In [1]:
from IPython.display import Image
Image(filename="D:/g.png", width=500, height=200)
Out[1]:
James/Peng Li
As we all know energy is very important for economic development of every country. It is the basis for GDP, but meanwhile energy consumption may cause CO2 emission, especially by coal and oil.We also would like to study the Forest Area per capita, because trees are the main way to capture CO2 emission and transform it into oxygen. Last but not least, we will study relationship between GDP and happiness indicator. Based on the data collection, we will study from 2010 to 2020 and focus on 10 representative countries.
from IPython.display import Image
Image(filename="D:/g.png", width=500, height=200)
The energy efficiency for GDP. This means for same energy consumption unit which country can achieve higher GDP?
The energy efficiency for CO2 emission. This means for same energy consumption unit which country can emit less CO2?
The compensation of forest for CO2 emission. Based on the CO2 emission, does the country have certain forest area to compensate the CO2 emission?
The influence of GDP for happiness. Does it mean higher GDP will leads to higher happiness?
Overall structure chart, please see below
Acquire datasets from different sources from excel file, from a web API and from web-scraped;
Wrangle the data into an usable format and perform EDA;
Integrate datasets into one;
persist the data into a SQLite relational database with a suitable schema;
Perform group-by queries, pivot tables, cross-tabulation of the data to answer your research questions, together with a rich set of visualisations;
Summary
import os
import pandas as pd
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style="ticks")
from pylab import rcParams
import pylab
%matplotlib inline
matplotlib.style.use('ggplot')
# Set some Pandas options as you like
pd.set_option('display.notebook_repr_html', True)
#this line enables the plots to be embedded into the notebook
rcParams['figure.figsize'] = 15, 10
rcParams['font.size'] = 20
rcParams['axes.facecolor'] = 'white'
pd.set_option('display.max_columns', None)
#we first need to make some extra imports
import json
from time import sleep
from datetime import datetime
import requests
from bs4 import BeautifulSoup
import pandas as pd
energy2010to2020 = pd.read_excel('./energy2010to2020.xls')
energy2010to2020
| Country_name | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Canada | 388.8 | 398.9 | 395.5 | 400.7 | 398.0 | 395.9 | 387.7 | 387.8 | 389.4 | 386.3 | 361.1 |
| 1 | Mexico | 64.1 | 66.2 | 65.7 | 65.1 | 64.0 | 63.1 | 63.1 | 63.3 | 62.1 | 59.2 | 50.2 |
| 2 | United States | 300.7 | 295.4 | 285.4 | 290.9 | 291.8 | 287.0 | 284.7 | 283.8 | 292.4 | 288.4 | 265.2 |
| 3 | Argentina | 79.1 | 80.7 | 82.9 | 85.2 | 84.2 | 84.9 | 83.5 | 82.9 | 80.9 | 75.5 | 69.7 |
| 4 | Brazil | 56.0 | 58.0 | 58.5 | 60.2 | 61.1 | 59.7 | 57.7 | 57.9 | 57.8 | 58.9 | 56.5 |
| 5 | Chile | 77.9 | 83.8 | 84.9 | 84.9 | 82.4 | 83.2 | 86.2 | 85.5 | 87.8 | 88.9 | 84.1 |
| 6 | Colombia | 31.8 | 32.5 | 34.5 | 34.4 | 35.8 | 35.7 | 37.1 | 37.1 | 37.3 | 37.9 | 34.7 |
| 7 | Ecuador | 36.8 | 38.4 | 39.9 | 40.6 | 42.0 | 41.2 | 40.3 | 40.9 | 42.5 | 42.8 | 36.6 |
| 8 | Peru | 28.0 | 30.7 | 31.4 | 31.7 | 32.2 | 33.3 | 35.1 | 35.4 | 36.7 | 36.5 | 30.2 |
| 9 | Trinidad & Tobago | 633.9 | 618.8 | 605.3 | 612.4 | 605.4 | 584.0 | 515.4 | 544.4 | 513.1 | 509.5 | 445.7 |
| 10 | Venezuela | 118.2 | 119.1 | 122.8 | 122.7 | 115.7 | 114.1 | 100.2 | 99.5 | 85.6 | 68.4 | 50.7 |
| 11 | Austria | 175.7 | 163.7 | 170.7 | 168.5 | 160.4 | 159.5 | 163.5 | 166.0 | 160.8 | 167.2 | 153.6 |
| 12 | Belgium | 252.6 | 234.2 | 223.0 | 227.6 | 210.2 | 211.9 | 227.1 | 228.2 | 225.3 | 231.2 | 189.0 |
| 13 | Czech Republic | 174.3 | 169.8 | 168.5 | 165.0 | 161.3 | 158.0 | 155.6 | 162.0 | 161.2 | 158.9 | 143.6 |
| 14 | Finland | 242.8 | 225.8 | 218.5 | 218.8 | 210.1 | 207.9 | 210.9 | 205.7 | 209.5 | 203.4 | 197.9 |
| 15 | France | 169.4 | 161.9 | 161.0 | 161.7 | 154.1 | 154.4 | 151.3 | 149.8 | 152.1 | 148.5 | 133.3 |
| 16 | Germany | 169.6 | 163.3 | 165.1 | 169.3 | 161.6 | 163.8 | 165.7 | 166.7 | 161.6 | 156.3 | 144.6 |
| 17 | Greece | 123.1 | 121.2 | 114.5 | 107.8 | 101.8 | 103.3 | 101.7 | 107.1 | 107.6 | 113.9 | 96.0 |
| 18 | Hungary | 99.8 | 97.2 | 90.9 | 86.5 | 86.6 | 91.5 | 93.8 | 98.7 | 99.6 | 101.2 | 100.2 |
| 19 | Italy | 122.6 | 119.6 | 115.6 | 109.7 | 103.3 | 106.0 | 106.3 | 107.5 | 108.4 | 106.5 | 97.0 |
| 20 | Netherlands | 245.5 | 234.4 | 225.9 | 218.5 | 205.7 | 208.0 | 211.3 | 207.5 | 206.8 | 205.4 | 196.8 |
| 21 | Norway | 354.0 | 354.3 | 386.3 | 358.0 | 363.9 | 364.4 | 364.5 | 362.9 | 356.2 | 330.6 | 356.0 |
| 22 | Poland | 109.1 | 109.8 | 106.6 | 107.1 | 103.3 | 104.5 | 109.3 | 113.7 | 115.1 | 111.8 | 106.0 |
| 23 | Portugal | 101.7 | 97.3 | 89.3 | 98.1 | 100.6 | 99.2 | 106.3 | 103.8 | 105.8 | 100.9 | 91.5 |
| 24 | Romania | 69.4 | 71.7 | 69.4 | 64.8 | 67.5 | 68.2 | 68.6 | 70.4 | 72.2 | 71.1 | 69.2 |
| 25 | Spain | 129.5 | 126.8 | 126.1 | 119.7 | 117.9 | 119.8 | 121.0 | 122.5 | 124.0 | 119.7 | 106.3 |
| 26 | Sweden | 229.8 | 225.2 | 236.6 | 220.3 | 217.5 | 222.6 | 217.3 | 222.8 | 216.6 | 223.4 | 217.8 |
| 27 | Switzerland | 157.4 | 147.6 | 153.8 | 155.9 | 146.8 | 142.0 | 132.3 | 131.4 | 132.3 | 136.9 | 124.5 |
| 28 | Turkey | 62.2 | 65.5 | 68.4 | 66.7 | 67.7 | 72.9 | 75.3 | 78.6 | 76.4 | 78.0 | 74.6 |
| 29 | Ukraine | 111.3 | 115.6 | 113.7 | 108.0 | 95.9 | 79.9 | 83.9 | 78.5 | 81.8 | 77.7 | 75.8 |
| 30 | United Kingdom | 140.5 | 131.6 | 132.1 | 130.5 | 122.1 | 122.7 | 120.5 | 119.3 | 118.4 | 114.4 | 101.6 |
| 31 | Azerbaijan | 51.9 | 57.0 | 58.0 | 58.8 | 59.2 | 64.0 | 62.6 | 60.7 | 61.9 | 64.5 | 61.3 |
| 32 | Belarus | 115.6 | 115.1 | 124.3 | 109.5 | 113.1 | 102.7 | 102.1 | 104.0 | 113.2 | 111.5 | 103.9 |
| 33 | Kazakhstan | 137.5 | 153.6 | 158.7 | 157.1 | 157.6 | 156.1 | 152.9 | 162.6 | 176.8 | 169.8 | 165.4 |
| 34 | Russian Federation | 195.1 | 201.2 | 201.3 | 198.5 | 198.5 | 194.7 | 198.4 | 199.3 | 206.6 | 204.9 | 194.0 |
| 35 | Turkmenistan | 176.6 | 192.7 | 206.4 | 180.0 | 183.1 | 215.3 | 209.5 | 203.9 | 223.4 | 240.1 | 232.7 |
| 36 | Uzbekistan | 66.0 | 67.4 | 65.4 | 65.4 | 66.4 | 62.4 | 58.7 | 57.9 | 59.0 | 58.2 | 56.0 |
| 37 | Iran | 118.2 | 122.1 | 121.9 | 124.8 | 128.9 | 126.5 | 130.8 | 133.8 | 139.6 | 144.4 | 143.2 |
| 38 | Iraq | 48.8 | 50.0 | 51.2 | 53.1 | 49.0 | 47.3 | 52.8 | 50.8 | 52.0 | 55.9 | 51.3 |
| 39 | Israel | 135.0 | 135.6 | 139.3 | 127.3 | 123.2 | 128.0 | 128.1 | 131.7 | 129.9 | 132.5 | 121.0 |
| 40 | Kuwait | 472.6 | 458.7 | 451.1 | 438.6 | 425.9 | 420.9 | 408.3 | 406.1 | 398.4 | 396.6 | 352.9 |
| 41 | Oman | 284.9 | 289.8 | 293.5 | 304.9 | 283.8 | 283.1 | 270.2 | 278.7 | 283.9 | 279.5 | 268.2 |
| 42 | Qatar | 646.7 | 686.1 | 726.4 | 740.3 | 759.6 | 829.6 | 783.2 | 740.8 | 639.7 | 679.7 | 594.2 |
| 43 | Saudi Arabia | 318.6 | 324.9 | 334.0 | 325.5 | 339.4 | 341.1 | 337.7 | 330.2 | 315.9 | 311.7 | 303.3 |
| 44 | United Arab Emirates | 409.2 | 410.7 | 423.2 | 443.9 | 438.2 | 481.9 | 495.9 | 490.6 | 476.7 | 466.0 | 423.7 |
| 45 | Algeria | 43.9 | 45.6 | 48.9 | 50.7 | 54.2 | 56.0 | 54.8 | 54.2 | 57.2 | 58.1 | 52.4 |
| 46 | Egypt | 39.2 | 39.1 | 40.2 | 39.0 | 38.1 | 38.0 | 39.1 | 39.4 | 39.2 | 38.5 | 35.6 |
| 47 | Morocco | 21.6 | 22.4 | 22.4 | 22.7 | 22.7 | 22.8 | 22.7 | 23.5 | 24.0 | 25.9 | 23.8 |
| 48 | Australia | 240.5 | 243.3 | 236.5 | 235.9 | 234.8 | 237.0 | 234.8 | 230.5 | 228.8 | 233.2 | 218.4 |
| 49 | Bangladesh | 6.1 | 6.6 | 6.9 | 7.1 | 7.3 | 8.4 | 8.4 | 8.6 | 9.1 | 10.1 | 9.7 |
| 50 | China | 76.2 | 81.8 | 84.6 | 87.2 | 89.2 | 89.9 | 91.0 | 93.5 | 96.4 | 99.1 | 101.1 |
| 51 | India | 18.2 | 19.0 | 19.8 | 20.3 | 21.4 | 21.9 | 22.6 | 23.3 | 24.5 | 24.8 | 23.2 |
| 52 | Indonesia | 26.5 | 28.1 | 29.5 | 30.0 | 27.5 | 27.4 | 27.4 | 28.2 | 30.1 | 32.0 | 29.6 |
| 53 | Japan | 164.2 | 155.8 | 154.9 | 153.7 | 149.9 | 147.9 | 146.4 | 148.3 | 147.8 | 144.8 | 134.7 |
| 54 | Malaysia | 118.8 | 121.1 | 128.3 | 132.5 | 131.9 | 132.0 | 137.1 | 137.2 | 137.3 | 138.7 | 127.1 |
| 55 | New Zealand | 188.9 | 187.9 | 187.1 | 186.2 | 192.6 | 192.3 | 191.7 | 193.2 | 191.1 | 194.4 | 174.3 |
| 56 | Pakistan | 14.8 | 14.4 | 13.2 | 14.0 | 14.2 | 14.6 | 15.6 | 16.2 | 16.4 | 16.2 | 15.7 |
| 57 | Philippines | 13.0 | 13.0 | 13.2 | 13.9 | 14.4 | 15.5 | 16.7 | 18.1 | 18.3 | 18.6 | 16.7 |
| 58 | Singapore | 559.5 | 567.1 | 558.3 | 561.8 | 570.5 | 599.5 | 615.3 | 628.8 | 626.3 | 607.8 | 583.9 |
| 59 | South Korea | 218.3 | 227.5 | 228.5 | 227.8 | 228.6 | 231.2 | 235.9 | 240.1 | 242.9 | 239.1 | 229.9 |
| 60 | Sri Lanka | 11.7 | 12.2 | 12.2 | 12.3 | 13.0 | 13.9 | 14.7 | 15.5 | 16.3 | 16.8 | 15.3 |
| 61 | Thailand | 65.3 | 67.5 | 71.8 | 72.7 | 74.3 | 75.8 | 77.1 | 78.2 | 79.6 | 79.2 | 73.3 |
| 62 | Vietnam | 21.3 | 24.0 | 24.9 | 25.9 | 28.1 | 30.9 | 33.0 | 35.0 | 39.0 | 43.2 | 42.0 |
| 63 | South Africa | 102.7 | 99.9 | 96.9 | 95.7 | 95.3 | 91.9 | 94.8 | 92.9 | 88.2 | 88.9 | 82.7 |
energy2010to2020 = pd.DataFrame(energy2010to2020 )
energy2010to2020 = energy2010to2020 .melt(id_vars=['Country_name'], var_name='year', value_name='Energy_consumption_per_capita')
print(energy2010to2020)
Country_name year Energy_consumption_per_capita 0 Canada 2010 388.8 1 Mexico 2010 64.1 2 United States 2010 300.7 3 Argentina 2010 79.1 4 Brazil 2010 56.0 5 Chile 2010 77.9 6 Colombia 2010 31.8 7 Ecuador 2010 36.8 8 Peru 2010 28.0 9 Trinidad & Tobago 2010 633.9 10 Venezuela 2010 118.2 11 Austria 2010 175.7 12 Belgium 2010 252.6 13 Czech Republic 2010 174.3 14 Finland 2010 242.8 15 France 2010 169.4 16 Germany 2010 169.6 17 Greece 2010 123.1 18 Hungary 2010 99.8 19 Italy 2010 122.6 20 Netherlands 2010 245.5 21 Norway 2010 354.0 22 Poland 2010 109.1 23 Portugal 2010 101.7 24 Romania 2010 69.4 25 Spain 2010 129.5 26 Sweden 2010 229.8 27 Switzerland 2010 157.4 28 Turkey 2010 62.2 29 Ukraine 2010 111.3 30 United Kingdom 2010 140.5 31 Azerbaijan 2010 51.9 32 Belarus 2010 115.6 33 Kazakhstan 2010 137.5 34 Russian Federation 2010 195.1 35 Turkmenistan 2010 176.6 36 Uzbekistan 2010 66.0 37 Iran 2010 118.2 38 Iraq 2010 48.8 39 Israel 2010 135.0 40 Kuwait 2010 472.6 41 Oman 2010 284.9 42 Qatar 2010 646.7 43 Saudi Arabia 2010 318.6 44 United Arab Emirates 2010 409.2 45 Algeria 2010 43.9 46 Egypt 2010 39.2 47 Morocco 2010 21.6 48 Australia 2010 240.5 49 Bangladesh 2010 6.1 50 China 2010 76.2 51 India 2010 18.2 52 Indonesia 2010 26.5 53 Japan 2010 164.2 54 Malaysia 2010 118.8 55 New Zealand 2010 188.9 56 Pakistan 2010 14.8 57 Philippines 2010 13.0 58 Singapore 2010 559.5 59 South Korea 2010 218.3 60 Sri Lanka 2010 11.7 61 Thailand 2010 65.3 62 Vietnam 2010 21.3 63 South Africa 2010 102.7 64 Canada 2011 398.9 65 Mexico 2011 66.2 66 United States 2011 295.4 67 Argentina 2011 80.7 68 Brazil 2011 58.0 69 Chile 2011 83.8 70 Colombia 2011 32.5 71 Ecuador 2011 38.4 72 Peru 2011 30.7 73 Trinidad & Tobago 2011 618.8 74 Venezuela 2011 119.1 75 Austria 2011 163.7 76 Belgium 2011 234.2 77 Czech Republic 2011 169.8 78 Finland 2011 225.8 79 France 2011 161.9 80 Germany 2011 163.3 81 Greece 2011 121.2 82 Hungary 2011 97.2 83 Italy 2011 119.6 84 Netherlands 2011 234.4 85 Norway 2011 354.3 86 Poland 2011 109.8 87 Portugal 2011 97.3 88 Romania 2011 71.7 89 Spain 2011 126.8 90 Sweden 2011 225.2 91 Switzerland 2011 147.6 92 Turkey 2011 65.5 93 Ukraine 2011 115.6 94 United Kingdom 2011 131.6 95 Azerbaijan 2011 57.0 96 Belarus 2011 115.1 97 Kazakhstan 2011 153.6 98 Russian Federation 2011 201.2 99 Turkmenistan 2011 192.7 100 Uzbekistan 2011 67.4 101 Iran 2011 122.1 102 Iraq 2011 50.0 103 Israel 2011 135.6 104 Kuwait 2011 458.7 105 Oman 2011 289.8 106 Qatar 2011 686.1 107 Saudi Arabia 2011 324.9 108 United Arab Emirates 2011 410.7 109 Algeria 2011 45.6 110 Egypt 2011 39.1 111 Morocco 2011 22.4 112 Australia 2011 243.3 113 Bangladesh 2011 6.6 114 China 2011 81.8 115 India 2011 19.0 116 Indonesia 2011 28.1 117 Japan 2011 155.8 118 Malaysia 2011 121.1 119 New Zealand 2011 187.9 120 Pakistan 2011 14.4 121 Philippines 2011 13.0 122 Singapore 2011 567.1 123 South Korea 2011 227.5 124 Sri Lanka 2011 12.2 125 Thailand 2011 67.5 126 Vietnam 2011 24.0 127 South Africa 2011 99.9 128 Canada 2012 395.5 129 Mexico 2012 65.7 130 United States 2012 285.4 131 Argentina 2012 82.9 132 Brazil 2012 58.5 133 Chile 2012 84.9 134 Colombia 2012 34.5 135 Ecuador 2012 39.9 136 Peru 2012 31.4 137 Trinidad & Tobago 2012 605.3 138 Venezuela 2012 122.8 139 Austria 2012 170.7 140 Belgium 2012 223.0 141 Czech Republic 2012 168.5 142 Finland 2012 218.5 143 France 2012 161.0 144 Germany 2012 165.1 145 Greece 2012 114.5 146 Hungary 2012 90.9 147 Italy 2012 115.6 148 Netherlands 2012 225.9 149 Norway 2012 386.3 150 Poland 2012 106.6 151 Portugal 2012 89.3 152 Romania 2012 69.4 153 Spain 2012 126.1 154 Sweden 2012 236.6 155 Switzerland 2012 153.8 156 Turkey 2012 68.4 157 Ukraine 2012 113.7 158 United Kingdom 2012 132.1 159 Azerbaijan 2012 58.0 160 Belarus 2012 124.3 161 Kazakhstan 2012 158.7 162 Russian Federation 2012 201.3 163 Turkmenistan 2012 206.4 164 Uzbekistan 2012 65.4 165 Iran 2012 121.9 166 Iraq 2012 51.2 167 Israel 2012 139.3 168 Kuwait 2012 451.1 169 Oman 2012 293.5 170 Qatar 2012 726.4 171 Saudi Arabia 2012 334.0 172 United Arab Emirates 2012 423.2 173 Algeria 2012 48.9 174 Egypt 2012 40.2 175 Morocco 2012 22.4 176 Australia 2012 236.5 177 Bangladesh 2012 6.9 178 China 2012 84.6 179 India 2012 19.8 180 Indonesia 2012 29.5 181 Japan 2012 154.9 182 Malaysia 2012 128.3 183 New Zealand 2012 187.1 184 Pakistan 2012 13.2 185 Philippines 2012 13.2 186 Singapore 2012 558.3 187 South Korea 2012 228.5 188 Sri Lanka 2012 12.2 189 Thailand 2012 71.8 190 Vietnam 2012 24.9 191 South Africa 2012 96.9 192 Canada 2013 400.7 193 Mexico 2013 65.1 194 United States 2013 290.9 195 Argentina 2013 85.2 196 Brazil 2013 60.2 197 Chile 2013 84.9 198 Colombia 2013 34.4 199 Ecuador 2013 40.6 200 Peru 2013 31.7 201 Trinidad & Tobago 2013 612.4 202 Venezuela 2013 122.7 203 Austria 2013 168.5 204 Belgium 2013 227.6 205 Czech Republic 2013 165.0 206 Finland 2013 218.8 207 France 2013 161.7 208 Germany 2013 169.3 209 Greece 2013 107.8 210 Hungary 2013 86.5 211 Italy 2013 109.7 212 Netherlands 2013 218.5 213 Norway 2013 358.0 214 Poland 2013 107.1 215 Portugal 2013 98.1 216 Romania 2013 64.8 217 Spain 2013 119.7 218 Sweden 2013 220.3 219 Switzerland 2013 155.9 220 Turkey 2013 66.7 221 Ukraine 2013 108.0 222 United Kingdom 2013 130.5 223 Azerbaijan 2013 58.8 224 Belarus 2013 109.5 225 Kazakhstan 2013 157.1 226 Russian Federation 2013 198.5 227 Turkmenistan 2013 180.0 228 Uzbekistan 2013 65.4 229 Iran 2013 124.8 230 Iraq 2013 53.1 231 Israel 2013 127.3 232 Kuwait 2013 438.6 233 Oman 2013 304.9 234 Qatar 2013 740.3 235 Saudi Arabia 2013 325.5 236 United Arab Emirates 2013 443.9 237 Algeria 2013 50.7 238 Egypt 2013 39.0 239 Morocco 2013 22.7 240 Australia 2013 235.9 241 Bangladesh 2013 7.1 242 China 2013 87.2 243 India 2013 20.3 244 Indonesia 2013 30.0 245 Japan 2013 153.7 246 Malaysia 2013 132.5 247 New Zealand 2013 186.2 248 Pakistan 2013 14.0 249 Philippines 2013 13.9 250 Singapore 2013 561.8 251 South Korea 2013 227.8 252 Sri Lanka 2013 12.3 253 Thailand 2013 72.7 254 Vietnam 2013 25.9 255 South Africa 2013 95.7 256 Canada 2014 398.0 257 Mexico 2014 64.0 258 United States 2014 291.8 259 Argentina 2014 84.2 260 Brazil 2014 61.1 261 Chile 2014 82.4 262 Colombia 2014 35.8 263 Ecuador 2014 42.0 264 Peru 2014 32.2 265 Trinidad & Tobago 2014 605.4 266 Venezuela 2014 115.7 267 Austria 2014 160.4 268 Belgium 2014 210.2 269 Czech Republic 2014 161.3 270 Finland 2014 210.1 271 France 2014 154.1 272 Germany 2014 161.6 273 Greece 2014 101.8 274 Hungary 2014 86.6 275 Italy 2014 103.3 276 Netherlands 2014 205.7 277 Norway 2014 363.9 278 Poland 2014 103.3 279 Portugal 2014 100.6 280 Romania 2014 67.5 281 Spain 2014 117.9 282 Sweden 2014 217.5 283 Switzerland 2014 146.8 284 Turkey 2014 67.7 285 Ukraine 2014 95.9 286 United Kingdom 2014 122.1 287 Azerbaijan 2014 59.2 288 Belarus 2014 113.1 289 Kazakhstan 2014 157.6 290 Russian Federation 2014 198.5 291 Turkmenistan 2014 183.1 292 Uzbekistan 2014 66.4 293 Iran 2014 128.9 294 Iraq 2014 49.0 295 Israel 2014 123.2 296 Kuwait 2014 425.9 297 Oman 2014 283.8 298 Qatar 2014 759.6 299 Saudi Arabia 2014 339.4 300 United Arab Emirates 2014 438.2 301 Algeria 2014 54.2 302 Egypt 2014 38.1 303 Morocco 2014 22.7 304 Australia 2014 234.8 305 Bangladesh 2014 7.3 306 China 2014 89.2 307 India 2014 21.4 308 Indonesia 2014 27.5 309 Japan 2014 149.9 310 Malaysia 2014 131.9 311 New Zealand 2014 192.6 312 Pakistan 2014 14.2 313 Philippines 2014 14.4 314 Singapore 2014 570.5 315 South Korea 2014 228.6 316 Sri Lanka 2014 13.0 317 Thailand 2014 74.3 318 Vietnam 2014 28.1 319 South Africa 2014 95.3 320 Canada 2015 395.9 321 Mexico 2015 63.1 322 United States 2015 287.0 323 Argentina 2015 84.9 324 Brazil 2015 59.7 325 Chile 2015 83.2 326 Colombia 2015 35.7 327 Ecuador 2015 41.2 328 Peru 2015 33.3 329 Trinidad & Tobago 2015 584.0 330 Venezuela 2015 114.1 331 Austria 2015 159.5 332 Belgium 2015 211.9 333 Czech Republic 2015 158.0 334 Finland 2015 207.9 335 France 2015 154.4 336 Germany 2015 163.8 337 Greece 2015 103.3 338 Hungary 2015 91.5 339 Italy 2015 106.0 340 Netherlands 2015 208.0 341 Norway 2015 364.4 342 Poland 2015 104.5 343 Portugal 2015 99.2 344 Romania 2015 68.2 345 Spain 2015 119.8 346 Sweden 2015 222.6 347 Switzerland 2015 142.0 348 Turkey 2015 72.9 349 Ukraine 2015 79.9 350 United Kingdom 2015 122.7 351 Azerbaijan 2015 64.0 352 Belarus 2015 102.7 353 Kazakhstan 2015 156.1 354 Russian Federation 2015 194.7 355 Turkmenistan 2015 215.3 356 Uzbekistan 2015 62.4 357 Iran 2015 126.5 358 Iraq 2015 47.3 359 Israel 2015 128.0 360 Kuwait 2015 420.9 361 Oman 2015 283.1 362 Qatar 2015 829.6 363 Saudi Arabia 2015 341.1 364 United Arab Emirates 2015 481.9 365 Algeria 2015 56.0 366 Egypt 2015 38.0 367 Morocco 2015 22.8 368 Australia 2015 237.0 369 Bangladesh 2015 8.4 370 China 2015 89.9 371 India 2015 21.9 372 Indonesia 2015 27.4 373 Japan 2015 147.9 374 Malaysia 2015 132.0 375 New Zealand 2015 192.3 376 Pakistan 2015 14.6 377 Philippines 2015 15.5 378 Singapore 2015 599.5 379 South Korea 2015 231.2 380 Sri Lanka 2015 13.9 381 Thailand 2015 75.8 382 Vietnam 2015 30.9 383 South Africa 2015 91.9 384 Canada 2016 387.7 385 Mexico 2016 63.1 386 United States 2016 284.7 387 Argentina 2016 83.5 388 Brazil 2016 57.7 389 Chile 2016 86.2 390 Colombia 2016 37.1 391 Ecuador 2016 40.3 392 Peru 2016 35.1 393 Trinidad & Tobago 2016 515.4 394 Venezuela 2016 100.2 395 Austria 2016 163.5 396 Belgium 2016 227.1 397 Czech Republic 2016 155.6 398 Finland 2016 210.9 399 France 2016 151.3 400 Germany 2016 165.7 401 Greece 2016 101.7 402 Hungary 2016 93.8 403 Italy 2016 106.3 404 Netherlands 2016 211.3 405 Norway 2016 364.5 406 Poland 2016 109.3 407 Portugal 2016 106.3 408 Romania 2016 68.6 409 Spain 2016 121.0 410 Sweden 2016 217.3 411 Switzerland 2016 132.3 412 Turkey 2016 75.3 413 Ukraine 2016 83.9 414 United Kingdom 2016 120.5 415 Azerbaijan 2016 62.6 416 Belarus 2016 102.1 417 Kazakhstan 2016 152.9 418 Russian Federation 2016 198.4 419 Turkmenistan 2016 209.5 420 Uzbekistan 2016 58.7 421 Iran 2016 130.8 422 Iraq 2016 52.8 423 Israel 2016 128.1 424 Kuwait 2016 408.3 425 Oman 2016 270.2 426 Qatar 2016 783.2 427 Saudi Arabia 2016 337.7 428 United Arab Emirates 2016 495.9 429 Algeria 2016 54.8 430 Egypt 2016 39.1 431 Morocco 2016 22.7 432 Australia 2016 234.8 433 Bangladesh 2016 8.4 434 China 2016 91.0 435 India 2016 22.6 436 Indonesia 2016 27.4 437 Japan 2016 146.4 438 Malaysia 2016 137.1 439 New Zealand 2016 191.7 440 Pakistan 2016 15.6 441 Philippines 2016 16.7 442 Singapore 2016 615.3 443 South Korea 2016 235.9 444 Sri Lanka 2016 14.7 445 Thailand 2016 77.1 446 Vietnam 2016 33.0 447 South Africa 2016 94.8 448 Canada 2017 387.8 449 Mexico 2017 63.3 450 United States 2017 283.8 451 Argentina 2017 82.9 452 Brazil 2017 57.9 453 Chile 2017 85.5 454 Colombia 2017 37.1 455 Ecuador 2017 40.9 456 Peru 2017 35.4 457 Trinidad & Tobago 2017 544.4 458 Venezuela 2017 99.5 459 Austria 2017 166.0 460 Belgium 2017 228.2 461 Czech Republic 2017 162.0 462 Finland 2017 205.7 463 France 2017 149.8 464 Germany 2017 166.7 465 Greece 2017 107.1 466 Hungary 2017 98.7 467 Italy 2017 107.5 468 Netherlands 2017 207.5 469 Norway 2017 362.9 470 Poland 2017 113.7 471 Portugal 2017 103.8 472 Romania 2017 70.4 473 Spain 2017 122.5 474 Sweden 2017 222.8 475 Switzerland 2017 131.4 476 Turkey 2017 78.6 477 Ukraine 2017 78.5 478 United Kingdom 2017 119.3 479 Azerbaijan 2017 60.7 480 Belarus 2017 104.0 481 Kazakhstan 2017 162.6 482 Russian Federation 2017 199.3 483 Turkmenistan 2017 203.9 484 Uzbekistan 2017 57.9 485 Iran 2017 133.8 486 Iraq 2017 50.8 487 Israel 2017 131.7 488 Kuwait 2017 406.1 489 Oman 2017 278.7 490 Qatar 2017 740.8 491 Saudi Arabia 2017 330.2 492 United Arab Emirates 2017 490.6 493 Algeria 2017 54.2 494 Egypt 2017 39.4 495 Morocco 2017 23.5 496 Australia 2017 230.5 497 Bangladesh 2017 8.6 498 China 2017 93.5 499 India 2017 23.3 500 Indonesia 2017 28.2 501 Japan 2017 148.3 502 Malaysia 2017 137.2 503 New Zealand 2017 193.2 504 Pakistan 2017 16.2 505 Philippines 2017 18.1 506 Singapore 2017 628.8 507 South Korea 2017 240.1 508 Sri Lanka 2017 15.5 509 Thailand 2017 78.2 510 Vietnam 2017 35.0 511 South Africa 2017 92.9 512 Canada 2018 389.4 513 Mexico 2018 62.1 514 United States 2018 292.4 515 Argentina 2018 80.9 516 Brazil 2018 57.8 517 Chile 2018 87.8 518 Colombia 2018 37.3 519 Ecuador 2018 42.5 520 Peru 2018 36.7 521 Trinidad & Tobago 2018 513.1 522 Venezuela 2018 85.6 523 Austria 2018 160.8 524 Belgium 2018 225.3 525 Czech Republic 2018 161.2 526 Finland 2018 209.5 527 France 2018 152.1 528 Germany 2018 161.6 529 Greece 2018 107.6 530 Hungary 2018 99.6 531 Italy 2018 108.4 532 Netherlands 2018 206.8 533 Norway 2018 356.2 534 Poland 2018 115.1 535 Portugal 2018 105.8 536 Romania 2018 72.2 537 Spain 2018 124.0 538 Sweden 2018 216.6 539 Switzerland 2018 132.3 540 Turkey 2018 76.4 541 Ukraine 2018 81.8 542 United Kingdom 2018 118.4 543 Azerbaijan 2018 61.9 544 Belarus 2018 113.2 545 Kazakhstan 2018 176.8 546 Russian Federation 2018 206.6 547 Turkmenistan 2018 223.4 548 Uzbekistan 2018 59.0 549 Iran 2018 139.6 550 Iraq 2018 52.0 551 Israel 2018 129.9 552 Kuwait 2018 398.4 553 Oman 2018 283.9 554 Qatar 2018 639.7 555 Saudi Arabia 2018 315.9 556 United Arab Emirates 2018 476.7 557 Algeria 2018 57.2 558 Egypt 2018 39.2 559 Morocco 2018 24.0 560 Australia 2018 228.8 561 Bangladesh 2018 9.1 562 China 2018 96.4 563 India 2018 24.5 564 Indonesia 2018 30.1 565 Japan 2018 147.8 566 Malaysia 2018 137.3 567 New Zealand 2018 191.1 568 Pakistan 2018 16.4 569 Philippines 2018 18.3 570 Singapore 2018 626.3 571 South Korea 2018 242.9 572 Sri Lanka 2018 16.3 573 Thailand 2018 79.6 574 Vietnam 2018 39.0 575 South Africa 2018 88.2 576 Canada 2019 386.3 577 Mexico 2019 59.2 578 United States 2019 288.4 579 Argentina 2019 75.5 580 Brazil 2019 58.9 581 Chile 2019 88.9 582 Colombia 2019 37.9 583 Ecuador 2019 42.8 584 Peru 2019 36.5 585 Trinidad & Tobago 2019 509.5 586 Venezuela 2019 68.4 587 Austria 2019 167.2 588 Belgium 2019 231.2 589 Czech Republic 2019 158.9 590 Finland 2019 203.4 591 France 2019 148.5 592 Germany 2019 156.3 593 Greece 2019 113.9 594 Hungary 2019 101.2 595 Italy 2019 106.5 596 Netherlands 2019 205.4 597 Norway 2019 330.6 598 Poland 2019 111.8 599 Portugal 2019 100.9 600 Romania 2019 71.1 601 Spain 2019 119.7 602 Sweden 2019 223.4 603 Switzerland 2019 136.9 604 Turkey 2019 78.0 605 Ukraine 2019 77.7 606 United Kingdom 2019 114.4 607 Azerbaijan 2019 64.5 608 Belarus 2019 111.5 609 Kazakhstan 2019 169.8 610 Russian Federation 2019 204.9 611 Turkmenistan 2019 240.1 612 Uzbekistan 2019 58.2 613 Iran 2019 144.4 614 Iraq 2019 55.9 615 Israel 2019 132.5 616 Kuwait 2019 396.6 617 Oman 2019 279.5 618 Qatar 2019 679.7 619 Saudi Arabia 2019 311.7 620 United Arab Emirates 2019 466.0 621 Algeria 2019 58.1 622 Egypt 2019 38.5 623 Morocco 2019 25.9 624 Australia 2019 233.2 625 Bangladesh 2019 10.1 626 China 2019 99.1 627 India 2019 24.8 628 Indonesia 2019 32.0 629 Japan 2019 144.8 630 Malaysia 2019 138.7 631 New Zealand 2019 194.4 632 Pakistan 2019 16.2 633 Philippines 2019 18.6 634 Singapore 2019 607.8 635 South Korea 2019 239.1 636 Sri Lanka 2019 16.8 637 Thailand 2019 79.2 638 Vietnam 2019 43.2 639 South Africa 2019 88.9 640 Canada 2020 361.1 641 Mexico 2020 50.2 642 United States 2020 265.2 643 Argentina 2020 69.7 644 Brazil 2020 56.5 645 Chile 2020 84.1 646 Colombia 2020 34.7 647 Ecuador 2020 36.6 648 Peru 2020 30.2 649 Trinidad & Tobago 2020 445.7 650 Venezuela 2020 50.7 651 Austria 2020 153.6 652 Belgium 2020 189.0 653 Czech Republic 2020 143.6 654 Finland 2020 197.9 655 France 2020 133.3 656 Germany 2020 144.6 657 Greece 2020 96.0 658 Hungary 2020 100.2 659 Italy 2020 97.0 660 Netherlands 2020 196.8 661 Norway 2020 356.0 662 Poland 2020 106.0 663 Portugal 2020 91.5 664 Romania 2020 69.2 665 Spain 2020 106.3 666 Sweden 2020 217.8 667 Switzerland 2020 124.5 668 Turkey 2020 74.6 669 Ukraine 2020 75.8 670 United Kingdom 2020 101.6 671 Azerbaijan 2020 61.3 672 Belarus 2020 103.9 673 Kazakhstan 2020 165.4 674 Russian Federation 2020 194.0 675 Turkmenistan 2020 232.7 676 Uzbekistan 2020 56.0 677 Iran 2020 143.2 678 Iraq 2020 51.3 679 Israel 2020 121.0 680 Kuwait 2020 352.9 681 Oman 2020 268.2 682 Qatar 2020 594.2 683 Saudi Arabia 2020 303.3 684 United Arab Emirates 2020 423.7 685 Algeria 2020 52.4 686 Egypt 2020 35.6 687 Morocco 2020 23.8 688 Australia 2020 218.4 689 Bangladesh 2020 9.7 690 China 2020 101.1 691 India 2020 23.2 692 Indonesia 2020 29.6 693 Japan 2020 134.7 694 Malaysia 2020 127.1 695 New Zealand 2020 174.3 696 Pakistan 2020 15.7 697 Philippines 2020 16.7 698 Singapore 2020 583.9 699 South Korea 2020 229.9 700 Sri Lanka 2020 15.3 701 Thailand 2020 73.3 702 Vietnam 2020 42.0 703 South Africa 2020 82.7
from IPython.core.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
C:\Users\lpxue\AppData\Local\Temp\ipykernel_19860\3777615979.py:1: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display from IPython.core.display import display, HTML
indicator = 'EN.ATM.CO2E.PC?date=2010:2020'
url = "http://api.worldbank.org/v2/countries/all/indicators/%s&format=json&per_page=5000" % indicator
response = requests.get(url)
result = response.content
result = json.loads(result)
worldbank_CO2 = pd.DataFrame.from_dict(result[1])
worldbank_CO2['country'] = worldbank_CO2[['country']].applymap(lambda x : x['value'])
worldbank_CO2.country.unique()
worldbank_CO2 = worldbank_CO2[['country', 'countryiso3code', 'date', 'value']]
worldbank_CO2.columns = ['Country_name', 'Countrycode', 'year', 'CO2_per_capita']
worldbank_CO2
| Country_name | Countrycode | year | CO2_per_capita | |
|---|---|---|---|---|
| 0 | Africa Eastern and Southern | AFE | 2020 | 0.795420 |
| 1 | Africa Eastern and Southern | AFE | 2019 | 0.915294 |
| 2 | Africa Eastern and Southern | AFE | 2018 | 0.921453 |
| 3 | Africa Eastern and Southern | AFE | 2017 | 0.933874 |
| 4 | Africa Eastern and Southern | AFE | 2016 | 0.941337 |
| 5 | Africa Eastern and Southern | AFE | 2015 | 0.960430 |
| 6 | Africa Eastern and Southern | AFE | 2014 | 1.013758 |
| 7 | Africa Eastern and Southern | AFE | 2013 | 1.001154 |
| 8 | Africa Eastern and Southern | AFE | 2012 | 0.989585 |
| 9 | Africa Eastern and Southern | AFE | 2011 | 0.976840 |
| 10 | Africa Eastern and Southern | AFE | 2010 | 1.017488 |
| 11 | Africa Western and Central | AFW | 2020 | 0.463150 |
| 12 | Africa Western and Central | AFW | 2019 | 0.490837 |
| 13 | Africa Western and Central | AFW | 2018 | 0.475817 |
| 14 | Africa Western and Central | AFW | 2017 | 0.465166 |
| 15 | Africa Western and Central | AFW | 2016 | 0.479775 |
| 16 | Africa Western and Central | AFW | 2015 | 0.475577 |
| 17 | Africa Western and Central | AFW | 2014 | 0.493505 |
| 18 | Africa Western and Central | AFW | 2013 | 0.481623 |
| 19 | Africa Western and Central | AFW | 2012 | 0.452101 |
| 20 | Africa Western and Central | AFW | 2011 | 0.451578 |
| 21 | Africa Western and Central | AFW | 2010 | 0.447817 |
| 22 | Arab World | ARB | 2020 | 3.929078 |
| 23 | Arab World | ARB | 2019 | 4.181158 |
| 24 | Arab World | ARB | 2018 | 4.222333 |
| 25 | Arab World | ARB | 2017 | 4.350684 |
| 26 | Arab World | ARB | 2016 | 4.402999 |
| 27 | Arab World | ARB | 2015 | 4.450525 |
| 28 | Arab World | ARB | 2014 | 4.439511 |
| 29 | Arab World | ARB | 2013 | 4.386231 |
| 30 | Arab World | ARB | 2012 | 4.401209 |
| 31 | Arab World | ARB | 2011 | 4.209484 |
| 32 | Arab World | ARB | 2010 | 4.208453 |
| 33 | Caribbean small states | CSS | 2020 | 4.402688 |
| 34 | Caribbean small states | CSS | 2019 | 5.066605 |
| 35 | Caribbean small states | CSS | 2018 | 5.125870 |
| 36 | Caribbean small states | CSS | 2017 | 4.971950 |
| 37 | Caribbean small states | CSS | 2016 | 5.123422 |
| 38 | Caribbean small states | CSS | 2015 | 5.437587 |
| 39 | Caribbean small states | CSS | 2014 | 5.582121 |
| 40 | Caribbean small states | CSS | 2013 | 5.672399 |
| 41 | Caribbean small states | CSS | 2012 | 5.518165 |
| 42 | Caribbean small states | CSS | 2011 | 5.630149 |
| 43 | Caribbean small states | CSS | 2010 | 5.468180 |
| 44 | Central Europe and the Baltics | CEB | 2020 | 5.857206 |
| 45 | Central Europe and the Baltics | CEB | 2019 | 6.285364 |
| 46 | Central Europe and the Baltics | CEB | 2018 | 6.616508 |
| 47 | Central Europe and the Baltics | CEB | 2017 | 6.658388 |
| 48 | Central Europe and the Baltics | CEB | 2016 | 6.376606 |
| 49 | Central Europe and the Baltics | CEB | 2015 | 6.244133 |
| 50 | Central Europe and the Baltics | CEB | 2014 | 6.139710 |
| 51 | Central Europe and the Baltics | CEB | 2013 | 6.323538 |
| 52 | Central Europe and the Baltics | CEB | 2012 | 6.564899 |
| 53 | Central Europe and the Baltics | CEB | 2011 | 6.810707 |
| 54 | Central Europe and the Baltics | CEB | 2010 | 6.784218 |
| 55 | Early-demographic dividend | EAR | 2020 | 2.016857 |
| 56 | Early-demographic dividend | EAR | 2019 | 2.203393 |
| 57 | Early-demographic dividend | EAR | 2018 | 2.241995 |
| 58 | Early-demographic dividend | EAR | 2017 | 2.218401 |
| 59 | Early-demographic dividend | EAR | 2016 | 2.166772 |
| 60 | Early-demographic dividend | EAR | 2015 | 2.160722 |
| 61 | Early-demographic dividend | EAR | 2014 | 2.172532 |
| 62 | Early-demographic dividend | EAR | 2013 | 2.097092 |
| 63 | Early-demographic dividend | EAR | 2012 | 2.103237 |
| 64 | Early-demographic dividend | EAR | 2011 | 2.034438 |
| 65 | Early-demographic dividend | EAR | 2010 | 1.988005 |
| 66 | East Asia & Pacific | EAS | 2020 | 6.221888 |
| 67 | East Asia & Pacific | EAS | 2019 | 6.246453 |
| 68 | East Asia & Pacific | EAS | 2018 | 6.166087 |
| 69 | East Asia & Pacific | EAS | 2017 | 5.960076 |
| 70 | East Asia & Pacific | EAS | 2016 | 5.864094 |
| 71 | East Asia & Pacific | EAS | 2015 | 5.888063 |
| 72 | East Asia & Pacific | EAS | 2014 | 5.987349 |
| 73 | East Asia & Pacific | EAS | 2013 | 6.010373 |
| 74 | East Asia & Pacific | EAS | 2012 | 5.857653 |
| 75 | East Asia & Pacific | EAS | 2011 | 5.752542 |
| 76 | East Asia & Pacific | EAS | 2010 | 5.367569 |
| 77 | East Asia & Pacific (excluding high income) | EAP | 2020 | 5.982246 |
| 78 | East Asia & Pacific (excluding high income) | EAP | 2019 | 5.951407 |
| 79 | East Asia & Pacific (excluding high income) | EAP | 2018 | 5.831680 |
| 80 | East Asia & Pacific (excluding high income) | EAP | 2017 | 5.578365 |
| 81 | East Asia & Pacific (excluding high income) | EAP | 2016 | 5.467821 |
| 82 | East Asia & Pacific (excluding high income) | EAP | 2015 | 5.490442 |
| 83 | East Asia & Pacific (excluding high income) | EAP | 2014 | 5.590427 |
| 84 | East Asia & Pacific (excluding high income) | EAP | 2013 | 5.575948 |
| 85 | East Asia & Pacific (excluding high income) | EAP | 2012 | 5.401485 |
| 86 | East Asia & Pacific (excluding high income) | EAP | 2011 | 5.299682 |
| 87 | East Asia & Pacific (excluding high income) | EAP | 2010 | 4.902680 |
| 88 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2020 | 6.031170 |
| 89 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2019 | 5.998371 |
| 90 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2018 | 5.879714 |
| 91 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2017 | 5.621201 |
| 92 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2016 | 5.522085 |
| 93 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2015 | 5.546539 |
| 94 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2014 | 5.644795 |
| 95 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2013 | 5.632025 |
| 96 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2012 | 5.450025 |
| 97 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2011 | 5.347773 |
| 98 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2010 | 4.938335 |
| 99 | Euro area | EMU | 2020 | 5.397825 |
| 100 | Euro area | EMU | 2019 | 6.047473 |
| 101 | Euro area | EMU | 2018 | 6.363281 |
| 102 | Euro area | EMU | 2017 | 6.542313 |
| 103 | Euro area | EMU | 2016 | 6.545927 |
| 104 | Euro area | EMU | 2015 | 6.564651 |
| 105 | Euro area | EMU | 2014 | 6.445446 |
| 106 | Euro area | EMU | 2013 | 6.830642 |
| 107 | Euro area | EMU | 2012 | 6.998146 |
| 108 | Euro area | EMU | 2011 | 7.101089 |
| 109 | Euro area | EMU | 2010 | 7.349038 |
| 110 | Europe & Central Asia | ECS | 2020 | 6.116715 |
| 111 | Europe & Central Asia | ECS | 2019 | 6.557131 |
| 112 | Europe & Central Asia | ECS | 2018 | 6.734357 |
| 113 | Europe & Central Asia | ECS | 2017 | 6.746232 |
| 114 | Europe & Central Asia | ECS | 2016 | 6.698063 |
| 115 | Europe & Central Asia | ECS | 2015 | 6.698998 |
| 116 | Europe & Central Asia | ECS | 2014 | 6.762496 |
| 117 | Europe & Central Asia | ECS | 2013 | 7.107362 |
| 118 | Europe & Central Asia | ECS | 2012 | 7.292913 |
| 119 | Europe & Central Asia | ECS | 2011 | 7.399038 |
| 120 | Europe & Central Asia | ECS | 2010 | 7.399863 |
| 121 | Europe & Central Asia (excluding high income) | ECA | 2020 | 7.075708 |
| 122 | Europe & Central Asia (excluding high income) | ECA | 2019 | 7.329478 |
| 123 | Europe & Central Asia (excluding high income) | ECA | 2018 | 7.344913 |
| 124 | Europe & Central Asia (excluding high income) | ECA | 2017 | 7.177088 |
| 125 | Europe & Central Asia (excluding high income) | ECA | 2016 | 7.059362 |
| 126 | Europe & Central Asia (excluding high income) | ECA | 2015 | 7.020077 |
| 127 | Europe & Central Asia (excluding high income) | ECA | 2014 | 7.246556 |
| 128 | Europe & Central Asia (excluding high income) | ECA | 2013 | 7.532727 |
| 129 | Europe & Central Asia (excluding high income) | ECA | 2012 | 7.720035 |
| 130 | Europe & Central Asia (excluding high income) | ECA | 2011 | 7.860238 |
| 131 | Europe & Central Asia (excluding high income) | ECA | 2010 | 7.493479 |
| 132 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2020 | 6.924813 |
| 133 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2019 | 7.189000 |
| 134 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2018 | 7.238844 |
| 135 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2017 | 7.093049 |
| 136 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2016 | 6.953000 |
| 137 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2015 | 6.895617 |
| 138 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2014 | 7.075619 |
| 139 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2013 | 7.350255 |
| 140 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2012 | 7.542709 |
| 141 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2011 | 7.685558 |
| 142 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2010 | 7.361746 |
| 143 | European Union | EUU | 2020 | 5.506070 |
| 144 | European Union | EUU | 2019 | 6.101852 |
| 145 | European Union | EUU | 2018 | 6.415939 |
| 146 | European Union | EUU | 2017 | 6.571147 |
| 147 | European Union | EUU | 2016 | 6.525933 |
| 148 | European Union | EUU | 2015 | 6.517123 |
| 149 | European Union | EUU | 2014 | 6.402090 |
| 150 | European Union | EUU | 2013 | 6.744306 |
| 151 | European Union | EUU | 2012 | 6.934679 |
| 152 | European Union | EUU | 2011 | 7.081678 |
| 153 | European Union | EUU | 2010 | 7.282944 |
| 154 | Fragile and conflict affected situations | FCS | 2020 | 0.775011 |
| 155 | Fragile and conflict affected situations | FCS | 2019 | 0.892138 |
| 156 | Fragile and conflict affected situations | FCS | 2018 | 0.925113 |
| 157 | Fragile and conflict affected situations | FCS | 2017 | 0.913743 |
| 158 | Fragile and conflict affected situations | FCS | 2016 | 0.943720 |
| 159 | Fragile and conflict affected situations | FCS | 2015 | 0.951757 |
| 160 | Fragile and conflict affected situations | FCS | 2014 | 1.071827 |
| 161 | Fragile and conflict affected situations | FCS | 2013 | 1.126579 |
| 162 | Fragile and conflict affected situations | FCS | 2012 | 1.134949 |
| 163 | Fragile and conflict affected situations | FCS | 2011 | 1.112796 |
| 164 | Fragile and conflict affected situations | FCS | 2010 | 1.135165 |
| 165 | Heavily indebted poor countries (HIPC) | HPC | 2020 | 0.268471 |
| 166 | Heavily indebted poor countries (HIPC) | HPC | 2019 | 0.289114 |
| 167 | Heavily indebted poor countries (HIPC) | HPC | 2018 | 0.279928 |
| 168 | Heavily indebted poor countries (HIPC) | HPC | 2017 | 0.275768 |
| 169 | Heavily indebted poor countries (HIPC) | HPC | 2016 | 0.273931 |
| 170 | Heavily indebted poor countries (HIPC) | HPC | 2015 | 0.267560 |
| 171 | Heavily indebted poor countries (HIPC) | HPC | 2014 | 0.258271 |
| 172 | Heavily indebted poor countries (HIPC) | HPC | 2013 | 0.250634 |
| 173 | Heavily indebted poor countries (HIPC) | HPC | 2012 | 0.245731 |
| 174 | Heavily indebted poor countries (HIPC) | HPC | 2011 | 0.239230 |
| 175 | Heavily indebted poor countries (HIPC) | HPC | 2010 | 0.227472 |
| 176 | High income | 2020 | 8.749965 | |
| 177 | High income | 2019 | 9.597279 | |
| 178 | High income | 2018 | 9.923941 | |
| 179 | High income | 2017 | 9.955496 | |
| 180 | High income | 2016 | 10.067645 | |
| 181 | High income | 2015 | 10.203247 | |
| 182 | High income | 2014 | 10.294485 | |
| 183 | High income | 2013 | 10.520093 | |
| 184 | High income | 2012 | 10.504752 | |
| 185 | High income | 2011 | 10.685107 | |
| 186 | High income | 2010 | 10.917085 | |
| 187 | IBRD only | IBD | 2020 | 4.304956 |
| 188 | IBRD only | IBD | 2019 | 4.440980 |
| 189 | IBRD only | IBD | 2018 | 4.424634 |
| 190 | IBRD only | IBD | 2017 | 4.293761 |
| 191 | IBRD only | IBD | 2016 | 4.228779 |
| 192 | IBRD only | IBD | 2015 | 4.253476 |
| 193 | IBRD only | IBD | 2014 | 4.340477 |
| 194 | IBRD only | IBD | 2013 | 4.332775 |
| 195 | IBRD only | IBD | 2012 | 4.259546 |
| 196 | IBRD only | IBD | 2011 | 4.178292 |
| 197 | IBRD only | IBD | 2010 | 3.952520 |
| 198 | IDA & IBRD total | IBT | 2020 | 3.298918 |
| 199 | IDA & IBRD total | IBT | 2019 | 3.418785 |
| 200 | IDA & IBRD total | IBT | 2018 | 3.417162 |
| 201 | IDA & IBRD total | IBT | 2017 | 3.329160 |
| 202 | IDA & IBRD total | IBT | 2016 | 3.284206 |
| 203 | IDA & IBRD total | IBT | 2015 | 3.304426 |
| 204 | IDA & IBRD total | IBT | 2014 | 3.377852 |
| 205 | IDA & IBRD total | IBT | 2013 | 3.377336 |
| 206 | IDA & IBRD total | IBT | 2012 | 3.329449 |
| 207 | IDA & IBRD total | IBT | 2011 | 3.280032 |
| 208 | IDA & IBRD total | IBT | 2010 | 3.116408 |
| 209 | IDA blend | IDB | 2020 | 0.798613 |
| 210 | IDA blend | IDB | 2019 | 0.839321 |
| 211 | IDA blend | IDB | 2018 | 0.841235 |
| 212 | IDA blend | IDB | 2017 | 0.860389 |
| 213 | IDA blend | IDB | 2016 | 0.840294 |
| 214 | IDA blend | IDB | 2015 | 0.806681 |
| 215 | IDA blend | IDB | 2014 | 0.822665 |
| 216 | IDA blend | IDB | 2013 | 0.817049 |
| 217 | IDA blend | IDB | 2012 | 0.801174 |
| 218 | IDA blend | IDB | 2011 | 0.847605 |
| 219 | IDA blend | IDB | 2010 | 0.845712 |
| 220 | IDA only | IDX | 2020 | 0.377941 |
| 221 | IDA only | IDX | 2019 | 0.403989 |
| 222 | IDA only | IDX | 2018 | 0.401070 |
| 223 | IDA only | IDX | 2017 | 0.386612 |
| 224 | IDA only | IDX | 2016 | 0.363940 |
| 225 | IDA only | IDX | 2015 | 0.341514 |
| 226 | IDA only | IDX | 2014 | 0.336121 |
| 227 | IDA only | IDX | 2013 | 0.325061 |
| 228 | IDA only | IDX | 2012 | 0.330849 |
| 229 | IDA only | IDX | 2011 | 0.330038 |
| 230 | IDA only | IDX | 2010 | 0.322044 |
| 231 | IDA total | IDA | 2020 | 0.517184 |
| 232 | IDA total | IDA | 2019 | 0.548328 |
| 233 | IDA total | IDA | 2018 | 0.547297 |
| 234 | IDA total | IDA | 2017 | 0.544303 |
| 235 | IDA total | IDA | 2016 | 0.522850 |
| 236 | IDA total | IDA | 2015 | 0.497056 |
| 237 | IDA total | IDA | 2014 | 0.499037 |
| 238 | IDA total | IDA | 2013 | 0.489904 |
| 239 | IDA total | IDA | 2012 | 0.488487 |
| 240 | IDA total | IDA | 2011 | 0.503542 |
| 241 | IDA total | IDA | 2010 | 0.497425 |
| 242 | Late-demographic dividend | LTE | 2020 | 6.683855 |
| 243 | Late-demographic dividend | LTE | 2019 | 6.697597 |
| 244 | Late-demographic dividend | LTE | 2018 | 6.595127 |
| 245 | Late-demographic dividend | LTE | 2017 | 6.375140 |
| 246 | Late-demographic dividend | LTE | 2016 | 6.279862 |
| 247 | Late-demographic dividend | LTE | 2015 | 6.315799 |
| 248 | Late-demographic dividend | LTE | 2014 | 6.429300 |
| 249 | Late-demographic dividend | LTE | 2013 | 6.467284 |
| 250 | Late-demographic dividend | LTE | 2012 | 6.298430 |
| 251 | Late-demographic dividend | LTE | 2011 | 6.200323 |
| 252 | Late-demographic dividend | LTE | 2010 | 5.796535 |
| 253 | Latin America & Caribbean | LCN | 2020 | 2.210611 |
| 254 | Latin America & Caribbean | LCN | 2019 | 2.511554 |
| 255 | Latin America & Caribbean | LCN | 2018 | 2.553937 |
| 256 | Latin America & Caribbean | LCN | 2017 | 2.660075 |
| 257 | Latin America & Caribbean | LCN | 2016 | 2.724731 |
| 258 | Latin America & Caribbean | LCN | 2015 | 2.817383 |
| 259 | Latin America & Caribbean | LCN | 2014 | 2.863165 |
| 260 | Latin America & Caribbean | LCN | 2013 | 2.878862 |
| 261 | Latin America & Caribbean | LCN | 2012 | 2.836071 |
| 262 | Latin America & Caribbean | LCN | 2011 | 2.745604 |
| 263 | Latin America & Caribbean | LCN | 2010 | 2.667140 |
| 264 | Latin America & Caribbean (excluding high income) | LAC | 2020 | 2.112545 |
| 265 | Latin America & Caribbean (excluding high income) | LAC | 2019 | 2.362844 |
| 266 | Latin America & Caribbean (excluding high income) | LAC | 2018 | 2.384924 |
| 267 | Latin America & Caribbean (excluding high income) | LAC | 2017 | 2.486043 |
| 268 | Latin America & Caribbean (excluding high income) | LAC | 2016 | 2.535947 |
| 269 | Latin America & Caribbean (excluding high income) | LAC | 2015 | 2.614646 |
| 270 | Latin America & Caribbean (excluding high income) | LAC | 2014 | 2.639996 |
| 271 | Latin America & Caribbean (excluding high income) | LAC | 2013 | 2.636526 |
| 272 | Latin America & Caribbean (excluding high income) | LAC | 2012 | 2.589658 |
| 273 | Latin America & Caribbean (excluding high income) | LAC | 2011 | 2.527890 |
| 274 | Latin America & Caribbean (excluding high income) | LAC | 2010 | 2.446084 |
| 275 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2020 | 2.221906 |
| 276 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2019 | 2.529702 |
| 277 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2018 | 2.569292 |
| 278 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2017 | 2.680728 |
| 279 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2016 | 2.746130 |
| 280 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2015 | 2.838107 |
| 281 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2014 | 2.889229 |
| 282 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2013 | 2.901367 |
| 283 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2012 | 2.858693 |
| 284 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2011 | 2.768261 |
| 285 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2010 | 2.687456 |
| 286 | Least developed countries: UN classification | LDC | 2020 | 0.327344 |
| 287 | Least developed countries: UN classification | LDC | 2019 | 0.353816 |
| 288 | Least developed countries: UN classification | LDC | 2018 | 0.351312 |
| 289 | Least developed countries: UN classification | LDC | 2017 | 0.340306 |
| 290 | Least developed countries: UN classification | LDC | 2016 | 0.321375 |
| 291 | Least developed countries: UN classification | LDC | 2015 | 0.301372 |
| 292 | Least developed countries: UN classification | LDC | 2014 | 0.296456 |
| 293 | Least developed countries: UN classification | LDC | 2013 | 0.282084 |
| 294 | Least developed countries: UN classification | LDC | 2012 | 0.265095 |
| 295 | Least developed countries: UN classification | LDC | 2011 | 0.258922 |
| 296 | Least developed countries: UN classification | LDC | 2010 | 0.249283 |
| 297 | Low & middle income | LMY | 2020 | 3.264621 |
| 298 | Low & middle income | LMY | 2019 | 3.375565 |
| 299 | Low & middle income | LMY | 2018 | 3.368286 |
| 300 | Low & middle income | LMY | 2017 | 3.277735 |
| 301 | Low & middle income | LMY | 2016 | 3.228409 |
| 302 | Low & middle income | LMY | 2015 | 3.247651 |
| 303 | Low & middle income | LMY | 2014 | 3.320846 |
| 304 | Low & middle income | LMY | 2013 | 3.315520 |
| 305 | Low & middle income | LMY | 2012 | 3.265756 |
| 306 | Low & middle income | LMY | 2011 | 3.216384 |
| 307 | Low & middle income | LMY | 2010 | 3.053585 |
| 308 | Low income | 2020 | 0.269341 | |
| 309 | Low income | 2019 | 0.294711 | |
| 310 | Low income | 2018 | 0.290268 | |
| 311 | Low income | 2017 | 0.291585 | |
| 312 | Low income | 2016 | 0.249648 | |
| 313 | Low income | 2015 | 0.248471 | |
| 314 | Low income | 2014 | 0.282727 | |
| 315 | Low income | 2013 | 0.280145 | |
| 316 | Low income | 2012 | 0.315320 | |
| 317 | Low income | 2011 | 0.346184 | |
| 318 | Low income | 2010 | 0.384135 | |
| 319 | Lower middle income | 2020 | 1.546117 | |
| 320 | Lower middle income | 2019 | 1.665768 | |
| 321 | Lower middle income | 2018 | 1.683221 | |
| 322 | Lower middle income | 2017 | 1.624199 | |
| 323 | Lower middle income | 2016 | 1.583105 | |
| 324 | Lower middle income | 2015 | 1.555548 | |
| 325 | Lower middle income | 2014 | 1.568248 | |
| 326 | Lower middle income | 2013 | 1.508235 | |
| 327 | Lower middle income | 2012 | 1.486155 | |
| 328 | Lower middle income | 2011 | 1.436674 | |
| 329 | Lower middle income | 2010 | 1.396224 | |
| 330 | Middle East & North Africa | MEA | 2020 | 5.033818 |
| 331 | Middle East & North Africa | MEA | 2019 | 5.301363 |
| 332 | Middle East & North Africa | MEA | 2018 | 5.376392 |
| 333 | Middle East & North Africa | MEA | 2017 | 5.496269 |
| 334 | Middle East & North Africa | MEA | 2016 | 5.516449 |
| 335 | Middle East & North Africa | MEA | 2015 | 5.569144 |
| 336 | Middle East & North Africa | MEA | 2014 | 5.603894 |
| 337 | Middle East & North Africa | MEA | 2013 | 5.537263 |
| 338 | Middle East & North Africa | MEA | 2012 | 5.537316 |
| 339 | Middle East & North Africa | MEA | 2011 | 5.351498 |
| 340 | Middle East & North Africa | MEA | 2010 | 5.348411 |
| 341 | Middle East & North Africa (excluding high inc... | MNA | 2020 | 3.329056 |
| 342 | Middle East & North Africa (excluding high inc... | MNA | 2019 | 3.552494 |
| 343 | Middle East & North Africa (excluding high inc... | MNA | 2018 | 3.639014 |
| 344 | Middle East & North Africa (excluding high inc... | MNA | 2017 | 3.631327 |
| 345 | Middle East & North Africa (excluding high inc... | MNA | 2016 | 3.550860 |
| 346 | Middle East & North Africa (excluding high inc... | MNA | 2015 | 3.569643 |
| 347 | Middle East & North Africa (excluding high inc... | MNA | 2014 | 3.669135 |
| 348 | Middle East & North Africa (excluding high inc... | MNA | 2013 | 3.654674 |
| 349 | Middle East & North Africa (excluding high inc... | MNA | 2012 | 3.642762 |
| 350 | Middle East & North Africa (excluding high inc... | MNA | 2011 | 3.541494 |
| 351 | Middle East & North Africa (excluding high inc... | MNA | 2010 | 3.588406 |
| 352 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2020 | 3.368344 |
| 353 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2019 | 3.594046 |
| 354 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2018 | 3.681235 |
| 355 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2017 | 3.673111 |
| 356 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2016 | 3.591594 |
| 357 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2015 | 3.610414 |
| 358 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2014 | 3.710907 |
| 359 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2013 | 3.696149 |
| 360 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2012 | 3.683920 |
| 361 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2011 | 3.581252 |
| 362 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2010 | 3.628421 |
| 363 | Middle income | MIC | 2020 | 3.604249 |
| 364 | Middle income | MIC | 2019 | 3.718555 |
| 365 | Middle income | MIC | 2018 | 3.704929 |
| 366 | Middle income | MIC | 2017 | 3.599013 |
| 367 | Middle income | MIC | 2016 | 3.543927 |
| 368 | Middle income | MIC | 2015 | 3.560634 |
| 369 | Middle income | MIC | 2014 | 3.633671 |
| 370 | Middle income | MIC | 2013 | 3.624159 |
| 371 | Middle income | MIC | 2012 | 3.561905 |
| 372 | Middle income | MIC | 2011 | 3.500222 |
| 373 | Middle income | MIC | 2010 | 3.313363 |
| 374 | North America | NAC | 2020 | 13.088837 |
| 375 | North America | NAC | 2019 | 14.709793 |
| 376 | North America | NAC | 2018 | 15.262019 |
| 377 | North America | NAC | 2017 | 14.893768 |
| 378 | North America | NAC | 2016 | 15.174494 |
| 379 | North America | NAC | 2015 | 15.566170 |
| 380 | North America | NAC | 2014 | 16.019064 |
| 381 | North America | NAC | 2013 | 16.081186 |
| 382 | North America | NAC | 2012 | 15.781555 |
| 383 | North America | NAC | 2011 | 16.540954 |
| 384 | North America | NAC | 2010 | 17.266308 |
| 385 | Not classified | 2020 | NaN | |
| 386 | Not classified | 2019 | NaN | |
| 387 | Not classified | 2018 | NaN | |
| 388 | Not classified | 2017 | NaN | |
| 389 | Not classified | 2016 | NaN | |
| 390 | Not classified | 2015 | NaN | |
| 391 | Not classified | 2014 | NaN | |
| 392 | Not classified | 2013 | NaN | |
| 393 | Not classified | 2012 | NaN | |
| 394 | Not classified | 2011 | NaN | |
| 395 | Not classified | 2010 | NaN | |
| 396 | OECD members | OED | 2020 | 7.718907 |
| 397 | OECD members | OED | 2019 | 8.520508 |
| 398 | OECD members | OED | 2018 | 8.845460 |
| 399 | OECD members | OED | 2017 | 8.878580 |
| 400 | OECD members | OED | 2016 | 8.952525 |
| 401 | OECD members | OED | 2015 | 9.060044 |
| 402 | OECD members | OED | 2014 | 9.164973 |
| 403 | OECD members | OED | 2013 | 9.402241 |
| 404 | OECD members | OED | 2012 | 9.414819 |
| 405 | OECD members | OED | 2011 | 9.607591 |
| 406 | OECD members | OED | 2010 | 9.833355 |
| 407 | Other small states | OSS | 2020 | 5.610562 |
| 408 | Other small states | OSS | 2019 | 5.907094 |
| 409 | Other small states | OSS | 2018 | 6.061552 |
| 410 | Other small states | OSS | 2017 | 6.177301 |
| 411 | Other small states | OSS | 2016 | 6.230073 |
| 412 | Other small states | OSS | 2015 | 6.234226 |
| 413 | Other small states | OSS | 2014 | 6.430822 |
| 414 | Other small states | OSS | 2013 | 6.283558 |
| 415 | Other small states | OSS | 2012 | 6.207735 |
| 416 | Other small states | OSS | 2011 | 6.124166 |
| 417 | Other small states | OSS | 2010 | 5.897833 |
| 418 | Pacific island small states | PSS | 2020 | 0.848521 |
| 419 | Pacific island small states | PSS | 2019 | 1.166845 |
| 420 | Pacific island small states | PSS | 2018 | 1.153402 |
| 421 | Pacific island small states | PSS | 2017 | 1.127336 |
| 422 | Pacific island small states | PSS | 2016 | 1.072905 |
| 423 | Pacific island small states | PSS | 2015 | 1.093761 |
| 424 | Pacific island small states | PSS | 2014 | 1.104224 |
| 425 | Pacific island small states | PSS | 2013 | 1.051210 |
| 426 | Pacific island small states | PSS | 2012 | 1.011450 |
| 427 | Pacific island small states | PSS | 2011 | 1.042761 |
| 428 | Pacific island small states | PSS | 2010 | 1.074867 |
| 429 | Post-demographic dividend | PST | 2020 | 8.551706 |
| 430 | Post-demographic dividend | PST | 2019 | 9.443542 |
| 431 | Post-demographic dividend | PST | 2018 | 9.802729 |
| 432 | Post-demographic dividend | PST | 2017 | 9.773058 |
| 433 | Post-demographic dividend | PST | 2016 | 9.897699 |
| 434 | Post-demographic dividend | PST | 2015 | 10.040145 |
| 435 | Post-demographic dividend | PST | 2014 | 10.213679 |
| 436 | Post-demographic dividend | PST | 2013 | 10.495813 |
| 437 | Post-demographic dividend | PST | 2012 | 10.477631 |
| 438 | Post-demographic dividend | PST | 2011 | 10.712276 |
| 439 | Post-demographic dividend | PST | 2010 | 10.970799 |
| 440 | Pre-demographic dividend | PRE | 2020 | 0.477025 |
| 441 | Pre-demographic dividend | PRE | 2019 | 0.528942 |
| 442 | Pre-demographic dividend | PRE | 2018 | 0.511820 |
| 443 | Pre-demographic dividend | PRE | 2017 | 0.502601 |
| 444 | Pre-demographic dividend | PRE | 2016 | 0.501719 |
| 445 | Pre-demographic dividend | PRE | 2015 | 0.494322 |
| 446 | Pre-demographic dividend | PRE | 2014 | 0.503899 |
| 447 | Pre-demographic dividend | PRE | 2013 | 0.502683 |
| 448 | Pre-demographic dividend | PRE | 2012 | 0.477038 |
| 449 | Pre-demographic dividend | PRE | 2011 | 0.465767 |
| 450 | Pre-demographic dividend | PRE | 2010 | 0.455614 |
| 451 | Small states | SST | 2020 | 5.110111 |
| 452 | Small states | SST | 2019 | 5.471941 |
| 453 | Small states | SST | 2018 | 5.597048 |
| 454 | Small states | SST | 2017 | 5.653121 |
| 455 | Small states | SST | 2016 | 5.712614 |
| 456 | Small states | SST | 2015 | 5.769475 |
| 457 | Small states | SST | 2014 | 5.939662 |
| 458 | Small states | SST | 2013 | 5.838170 |
| 459 | Small states | SST | 2012 | 5.745894 |
| 460 | Small states | SST | 2011 | 5.704188 |
| 461 | Small states | SST | 2010 | 5.504514 |
| 462 | South Asia | SAS | 2020 | 1.337791 |
| 463 | South Asia | SAS | 2019 | 1.478650 |
| 464 | South Asia | SAS | 2018 | 1.516961 |
| 465 | South Asia | SAS | 2017 | 1.453867 |
| 466 | South Asia | SAS | 2016 | 1.393034 |
| 467 | South Asia | SAS | 2015 | 1.370958 |
| 468 | South Asia | SAS | 2014 | 1.370498 |
| 469 | South Asia | SAS | 2013 | 1.278157 |
| 470 | South Asia | SAS | 2012 | 1.257016 |
| 471 | South Asia | SAS | 2011 | 1.179343 |
| 472 | South Asia | SAS | 2010 | 1.131311 |
| 473 | South Asia (IDA & IBRD) | TSA | 2020 | 1.337791 |
| 474 | South Asia (IDA & IBRD) | TSA | 2019 | 1.478650 |
| 475 | South Asia (IDA & IBRD) | TSA | 2018 | 1.516961 |
| 476 | South Asia (IDA & IBRD) | TSA | 2017 | 1.453867 |
| 477 | South Asia (IDA & IBRD) | TSA | 2016 | 1.393034 |
| 478 | South Asia (IDA & IBRD) | TSA | 2015 | 1.370958 |
| 479 | South Asia (IDA & IBRD) | TSA | 2014 | 1.370498 |
| 480 | South Asia (IDA & IBRD) | TSA | 2013 | 1.278157 |
| 481 | South Asia (IDA & IBRD) | TSA | 2012 | 1.257016 |
| 482 | South Asia (IDA & IBRD) | TSA | 2011 | 1.179343 |
| 483 | South Asia (IDA & IBRD) | TSA | 2010 | 1.131311 |
| 484 | Sub-Saharan Africa | SSF | 2020 | 0.660876 |
| 485 | Sub-Saharan Africa | SSF | 2019 | 0.743359 |
| 486 | Sub-Saharan Africa | SSF | 2018 | 0.740880 |
| 487 | Sub-Saharan Africa | SSF | 2017 | 0.743930 |
| 488 | Sub-Saharan Africa | SSF | 2016 | 0.754344 |
| 489 | Sub-Saharan Africa | SSF | 2015 | 0.763984 |
| 490 | Sub-Saharan Africa | SSF | 2014 | 0.802872 |
| 491 | Sub-Saharan Africa | SSF | 2013 | 0.790532 |
| 492 | Sub-Saharan Africa | SSF | 2012 | 0.771661 |
| 493 | Sub-Saharan Africa | SSF | 2011 | 0.763961 |
| 494 | Sub-Saharan Africa | SSF | 2010 | 0.786758 |
| 495 | Sub-Saharan Africa (excluding high income) | SSA | 2020 | 0.660413 |
| 496 | Sub-Saharan Africa (excluding high income) | SSA | 2019 | 0.742893 |
| 497 | Sub-Saharan Africa (excluding high income) | SSA | 2018 | 0.740394 |
| 498 | Sub-Saharan Africa (excluding high income) | SSA | 2017 | 0.743461 |
| 499 | Sub-Saharan Africa (excluding high income) | SSA | 2016 | 0.753867 |
| 500 | Sub-Saharan Africa (excluding high income) | SSA | 2015 | 0.763559 |
| 501 | Sub-Saharan Africa (excluding high income) | SSA | 2014 | 0.802482 |
| 502 | Sub-Saharan Africa (excluding high income) | SSA | 2013 | 0.790174 |
| 503 | Sub-Saharan Africa (excluding high income) | SSA | 2012 | 0.771278 |
| 504 | Sub-Saharan Africa (excluding high income) | SSA | 2011 | 0.763584 |
| 505 | Sub-Saharan Africa (excluding high income) | SSA | 2010 | 0.786334 |
| 506 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2020 | 0.660876 |
| 507 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2019 | 0.743359 |
| 508 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2018 | 0.740880 |
| 509 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2017 | 0.743930 |
| 510 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2016 | 0.754344 |
| 511 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2015 | 0.763984 |
| 512 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2014 | 0.802872 |
| 513 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2013 | 0.790532 |
| 514 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2012 | 0.771661 |
| 515 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2011 | 0.763961 |
| 516 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2010 | 0.786758 |
| 517 | Upper middle income | 2020 | 5.923960 | |
| 518 | Upper middle income | 2019 | 6.012487 | |
| 519 | Upper middle income | 2018 | 5.947017 | |
| 520 | Upper middle income | 2017 | 5.773008 | |
| 521 | Upper middle income | 2016 | 5.687045 | |
| 522 | Upper middle income | 2015 | 5.735859 | |
| 523 | Upper middle income | 2014 | 5.857718 | |
| 524 | Upper middle income | 2013 | 5.885588 | |
| 525 | Upper middle income | 2012 | 5.764482 | |
| 526 | Upper middle income | 2011 | 5.673918 | |
| 527 | Upper middle income | 2010 | 5.315663 | |
| 528 | World | WLD | 2020 | 4.292269 |
| 529 | World | WLD | 2019 | 4.582573 |
| 530 | World | WLD | 2018 | 4.642145 |
| 531 | World | WLD | 2017 | 4.578381 |
| 532 | World | WLD | 2016 | 4.558579 |
| 533 | World | WLD | 2015 | 4.601684 |
| 534 | World | WLD | 2014 | 4.682408 |
| 535 | World | WLD | 2013 | 4.719666 |
| 536 | World | WLD | 2012 | 4.685377 |
| 537 | World | WLD | 2011 | 4.689469 |
| 538 | World | WLD | 2010 | 4.604869 |
| 539 | Afghanistan | AFG | 2020 | 0.223479 |
| 540 | Afghanistan | AFG | 2019 | 0.297564 |
| 541 | Afghanistan | AFG | 2018 | 0.299083 |
| 542 | Afghanistan | AFG | 2017 | 0.281196 |
| 543 | Afghanistan | AFG | 2016 | 0.268359 |
| 544 | Afghanistan | AFG | 2015 | 0.297972 |
| 545 | Afghanistan | AFG | 2014 | 0.283692 |
| 546 | Afghanistan | AFG | 2013 | 0.298088 |
| 547 | Afghanistan | AFG | 2012 | 0.335061 |
| 548 | Afghanistan | AFG | 2011 | 0.408965 |
| 549 | Afghanistan | AFG | 2010 | 0.304230 |
| 550 | Albania | ALB | 2020 | 1.544550 |
| 551 | Albania | ALB | 2019 | 1.749462 |
| 552 | Albania | ALB | 2018 | 1.854642 |
| 553 | Albania | ALB | 2017 | 1.880557 |
| 554 | Albania | ALB | 2016 | 1.590069 |
| 555 | Albania | ALB | 2015 | 1.665219 |
| 556 | Albania | ALB | 2014 | 1.795712 |
| 557 | Albania | ALB | 2013 | 1.656390 |
| 558 | Albania | ALB | 2012 | 1.565921 |
| 559 | Albania | ALB | 2011 | 1.768109 |
| 560 | Albania | ALB | 2010 | 1.642762 |
| 561 | Algeria | DZA | 2020 | 3.718223 |
| 562 | Algeria | DZA | 2019 | 3.994402 |
| 563 | Algeria | DZA | 2018 | 3.924299 |
| 564 | Algeria | DZA | 2017 | 3.833681 |
| 565 | Algeria | DZA | 2016 | 3.833834 |
| 566 | Algeria | DZA | 2015 | 3.951961 |
| 567 | Algeria | DZA | 2014 | 3.811521 |
| 568 | Algeria | DZA | 2013 | 3.658469 |
| 569 | Algeria | DZA | 2012 | 3.621368 |
| 570 | Algeria | DZA | 2011 | 3.305233 |
| 571 | Algeria | DZA | 2010 | 3.184357 |
| 572 | American Samoa | ASM | 2020 | NaN |
| 573 | American Samoa | ASM | 2019 | NaN |
| 574 | American Samoa | ASM | 2018 | NaN |
| 575 | American Samoa | ASM | 2017 | NaN |
| 576 | American Samoa | ASM | 2016 | NaN |
| 577 | American Samoa | ASM | 2015 | NaN |
| 578 | American Samoa | ASM | 2014 | NaN |
| 579 | American Samoa | ASM | 2013 | NaN |
| 580 | American Samoa | ASM | 2012 | NaN |
| 581 | American Samoa | ASM | 2011 | NaN |
| 582 | American Samoa | ASM | 2010 | NaN |
| 583 | Andorra | AND | 2020 | 5.777148 |
| 584 | Andorra | AND | 2019 | 6.287204 |
| 585 | Andorra | AND | 2018 | 6.594057 |
| 586 | Andorra | AND | 2017 | 6.302098 |
| 587 | Andorra | AND | 2016 | 6.465288 |
| 588 | Andorra | AND | 2015 | 6.485769 |
| 589 | Andorra | AND | 2014 | 6.445931 |
| 590 | Andorra | AND | 2013 | 6.674233 |
| 591 | Andorra | AND | 2012 | 6.862293 |
| 592 | Andorra | AND | 2011 | 6.957586 |
| 593 | Andorra | AND | 2010 | 7.223591 |
| 594 | Angola | AGO | 2020 | 0.592743 |
| 595 | Angola | AGO | 2019 | 0.753638 |
| 596 | Angola | AGO | 2018 | 0.755828 |
| 597 | Angola | AGO | 2017 | 0.829723 |
| 598 | Angola | AGO | 2016 | 1.012552 |
| 599 | Angola | AGO | 2015 | 1.125185 |
| 600 | Angola | AGO | 2014 | 1.091497 |
| 601 | Angola | AGO | 2013 | 1.031044 |
| 602 | Angola | AGO | 2012 | 0.947583 |
| 603 | Angola | AGO | 2011 | 0.983787 |
| 604 | Angola | AGO | 2010 | 0.975917 |
| 605 | Antigua and Barbuda | ATG | 2020 | 5.121730 |
| 606 | Antigua and Barbuda | ATG | 2019 | 5.525582 |
| 607 | Antigua and Barbuda | ATG | 2018 | 5.550826 |
| 608 | Antigua and Barbuda | ATG | 2017 | 5.488427 |
| 609 | Antigua and Barbuda | ATG | 2016 | 5.526479 |
| 610 | Antigua and Barbuda | ATG | 2015 | 5.450240 |
| 611 | Antigua and Barbuda | ATG | 2014 | 5.340894 |
| 612 | Antigua and Barbuda | ATG | 2013 | 5.343684 |
| 613 | Antigua and Barbuda | ATG | 2012 | 5.359628 |
| 614 | Antigua and Barbuda | ATG | 2011 | 5.258910 |
| 615 | Antigua and Barbuda | ATG | 2010 | 5.435556 |
| 616 | Argentina | ARG | 2020 | 3.405618 |
| 617 | Argentina | ARG | 2019 | 3.742030 |
| 618 | Argentina | ARG | 2018 | 3.975651 |
| 619 | Argentina | ARG | 2017 | 4.070112 |
| 620 | Argentina | ARG | 2016 | 4.201816 |
| 621 | Argentina | ARG | 2015 | 4.301914 |
| 622 | Argentina | ARG | 2014 | 4.209112 |
| 623 | Argentina | ARG | 2013 | 4.342250 |
| 624 | Argentina | ARG | 2012 | 4.264111 |
| 625 | Argentina | ARG | 2011 | 4.281028 |
| 626 | Argentina | ARG | 2010 | 4.099844 |
| 627 | Armenia | ARM | 2020 | 2.404684 |
| 628 | Armenia | ARM | 2019 | 2.196552 |
| 629 | Armenia | ARM | 2018 | 2.013779 |
| 630 | Armenia | ARM | 2017 | 1.883396 |
| 631 | Armenia | ARM | 2016 | 1.767966 |
| 632 | Armenia | ARM | 2015 | 1.856253 |
| 633 | Armenia | ARM | 2014 | 1.895894 |
| 634 | Armenia | ARM | 2013 | 1.896163 |
| 635 | Armenia | ARM | 2012 | 1.961453 |
| 636 | Armenia | ARM | 2011 | 1.685606 |
| 637 | Armenia | ARM | 2010 | 1.471883 |
| 638 | Aruba | ABW | 2020 | NaN |
| 639 | Aruba | ABW | 2019 | NaN |
| 640 | Aruba | ABW | 2018 | NaN |
| 641 | Aruba | ABW | 2017 | NaN |
| 642 | Aruba | ABW | 2016 | NaN |
| 643 | Aruba | ABW | 2015 | NaN |
| 644 | Aruba | ABW | 2014 | NaN |
| 645 | Aruba | ABW | 2013 | NaN |
| 646 | Aruba | ABW | 2012 | NaN |
| 647 | Aruba | ABW | 2011 | NaN |
| 648 | Aruba | ABW | 2010 | NaN |
| 649 | Australia | AUS | 2020 | 14.776137 |
| 650 | Australia | AUS | 2019 | 15.599045 |
| 651 | Australia | AUS | 2018 | 15.865714 |
| 652 | Australia | AUS | 2017 | 16.149150 |
| 653 | Australia | AUS | 2016 | 16.320331 |
| 654 | Australia | AUS | 2015 | 16.198458 |
| 655 | Australia | AUS | 2014 | 16.155745 |
| 656 | Australia | AUS | 2013 | 16.794588 |
| 657 | Australia | AUS | 2012 | 17.405618 |
| 658 | Australia | AUS | 2011 | 17.656055 |
| 659 | Australia | AUS | 2010 | 17.973752 |
| 660 | Austria | AUT | 2020 | 6.632646 |
| 661 | Austria | AUT | 2019 | 7.263331 |
| 662 | Austria | AUT | 2018 | 7.141140 |
| 663 | Austria | AUT | 2017 | 7.487037 |
| 664 | Austria | AUT | 2016 | 7.290777 |
| 665 | Austria | AUT | 2015 | 7.318860 |
| 666 | Austria | AUT | 2014 | 7.260931 |
| 667 | Austria | AUT | 2013 | 7.754018 |
| 668 | Austria | AUT | 2012 | 7.723852 |
| 669 | Austria | AUT | 2011 | 8.136190 |
| 670 | Austria | AUT | 2010 | 8.365625 |
| 671 | Azerbaijan | AZE | 2020 | 3.398850 |
| 672 | Azerbaijan | AZE | 2019 | 3.543495 |
| 673 | Azerbaijan | AZE | 2018 | 3.292641 |
| 674 | Azerbaijan | AZE | 2017 | 3.243038 |
| 675 | Azerbaijan | AZE | 2016 | 3.303958 |
| 676 | Azerbaijan | AZE | 2015 | 3.292795 |
| 677 | Azerbaijan | AZE | 2014 | 3.381556 |
| 678 | Azerbaijan | AZE | 2013 | 3.285574 |
| 679 | Azerbaijan | AZE | 2012 | 3.239167 |
| 680 | Azerbaijan | AZE | 2011 | 2.974148 |
| 681 | Azerbaijan | AZE | 2010 | 2.685112 |
| 682 | Bahamas, The | BHS | 2020 | 6.042251 |
| 683 | Bahamas, The | BHS | 2019 | 6.482894 |
| 684 | Bahamas, The | BHS | 2018 | 6.955358 |
| 685 | Bahamas, The | BHS | 2017 | 5.438825 |
| 686 | Bahamas, The | BHS | 2016 | 5.153595 |
| 687 | Bahamas, The | BHS | 2015 | 5.621128 |
| 688 | Bahamas, The | BHS | 2014 | 6.473141 |
| 689 | Bahamas, The | BHS | 2013 | 7.274472 |
| 690 | Bahamas, The | BHS | 2012 | 6.266800 |
| 691 | Bahamas, The | BHS | 2011 | 5.775896 |
| 692 | Bahamas, The | BHS | 2010 | 5.302835 |
| 693 | Bahrain | BHR | 2020 | 21.976908 |
| 694 | Bahrain | BHR | 2019 | 22.063355 |
| 695 | Bahrain | BHR | 2018 | 20.737962 |
| 696 | Bahrain | BHR | 2017 | 20.946038 |
| 697 | Bahrain | BHR | 2016 | 21.495310 |
| 698 | Bahrain | BHR | 2015 | 22.385625 |
| 699 | Bahrain | BHR | 2014 | 23.096571 |
| 700 | Bahrain | BHR | 2013 | 22.868842 |
| 701 | Bahrain | BHR | 2012 | 22.184125 |
| 702 | Bahrain | BHR | 2011 | 21.465303 |
| 703 | Bahrain | BHR | 2010 | 21.394807 |
| 704 | Bangladesh | BGD | 2020 | 0.510648 |
| 705 | Bangladesh | BGD | 2019 | 0.559734 |
| 706 | Bangladesh | BGD | 2018 | 0.586158 |
| 707 | Bangladesh | BGD | 2017 | 0.541788 |
| 708 | Bangladesh | BGD | 2016 | 0.507739 |
| 709 | Bangladesh | BGD | 2015 | 0.463517 |
| 710 | Bangladesh | BGD | 2014 | 0.425189 |
| 711 | Bangladesh | BGD | 2013 | 0.408788 |
| 712 | Bangladesh | BGD | 2012 | 0.387829 |
| 713 | Bangladesh | BGD | 2011 | 0.361557 |
| 714 | Bangladesh | BGD | 2010 | 0.340233 |
| 715 | Barbados | BRB | 2020 | 3.904871 |
| 716 | Barbados | BRB | 2019 | 4.166143 |
| 717 | Barbados | BRB | 2018 | 4.541382 |
| 718 | Barbados | BRB | 2017 | 4.226450 |
| 719 | Barbados | BRB | 2016 | 4.632243 |
| 720 | Barbados | BRB | 2015 | 4.565435 |
| 721 | Barbados | BRB | 2014 | 4.620189 |
| 722 | Barbados | BRB | 2013 | 5.199176 |
| 723 | Barbados | BRB | 2012 | 5.313671 |
| 724 | Barbados | BRB | 2011 | 5.503909 |
| 725 | Barbados | BRB | 2010 | 5.392940 |
| 726 | Belarus | BLR | 2020 | 5.842407 |
| 727 | Belarus | BLR | 2019 | 6.123427 |
| 728 | Belarus | BLR | 2018 | 6.279579 |
| 729 | Belarus | BLR | 2017 | 5.946407 |
| 730 | Belarus | BLR | 2016 | 5.829464 |
| 731 | Belarus | BLR | 2015 | 5.799689 |
| 732 | Belarus | BLR | 2014 | 6.290068 |
| 733 | Belarus | BLR | 2013 | 6.342249 |
| 734 | Belarus | BLR | 2012 | 6.323630 |
| 735 | Belarus | BLR | 2011 | 6.164447 |
| 736 | Belarus | BLR | 2010 | 6.478781 |
| 737 | Belgium | BEL | 2020 | 7.398131 |
| 738 | Belgium | BEL | 2019 | 8.093791 |
| 739 | Belgium | BEL | 2018 | 8.184367 |
| 740 | Belgium | BEL | 2017 | 8.139439 |
| 741 | Belgium | BEL | 2016 | 8.310660 |
| 742 | Belgium | BEL | 2015 | 8.434837 |
| 743 | Belgium | BEL | 2014 | 8.061552 |
| 744 | Belgium | BEL | 2013 | 8.651947 |
| 745 | Belgium | BEL | 2012 | 8.578030 |
| 746 | Belgium | BEL | 2011 | 8.741248 |
| 747 | Belgium | BEL | 2010 | 9.808816 |
| 748 | Belize | BLZ | 2020 | 1.741108 |
| 749 | Belize | BLZ | 2019 | 1.892083 |
| 750 | Belize | BLZ | 2018 | 1.648930 |
| 751 | Belize | BLZ | 2017 | 1.716338 |
| 752 | Belize | BLZ | 2016 | 1.773147 |
| 753 | Belize | BLZ | 2015 | 1.875950 |
| 754 | Belize | BLZ | 2014 | 1.372841 |
| 755 | Belize | BLZ | 2013 | 1.326997 |
| 756 | Belize | BLZ | 2012 | 1.380470 |
| 757 | Belize | BLZ | 2011 | 1.740012 |
| 758 | Belize | BLZ | 2010 | 1.649147 |
| 759 | Benin | BEN | 2020 | 0.631205 |
| 760 | Benin | BEN | 2019 | 0.608237 |
| 761 | Benin | BEN | 2018 | 0.636814 |
| 762 | Benin | BEN | 2017 | 0.592941 |
| 763 | Benin | BEN | 2016 | 0.598486 |
| 764 | Benin | BEN | 2015 | 0.503586 |
| 765 | Benin | BEN | 2014 | 0.488571 |
| 766 | Benin | BEN | 2013 | 0.453635 |
| 767 | Benin | BEN | 2012 | 0.443845 |
| 768 | Benin | BEN | 2011 | 0.478349 |
| 769 | Benin | BEN | 2010 | 0.510824 |
| 770 | Bermuda | BMU | 2020 | NaN |
| 771 | Bermuda | BMU | 2019 | NaN |
| 772 | Bermuda | BMU | 2018 | NaN |
| 773 | Bermuda | BMU | 2017 | NaN |
| 774 | Bermuda | BMU | 2016 | NaN |
| 775 | Bermuda | BMU | 2015 | NaN |
| 776 | Bermuda | BMU | 2014 | NaN |
| 777 | Bermuda | BMU | 2013 | NaN |
| 778 | Bermuda | BMU | 2012 | NaN |
| 779 | Bermuda | BMU | 2011 | NaN |
| 780 | Bermuda | BMU | 2010 | NaN |
| 781 | Bhutan | BTN | 2020 | 1.340054 |
| 782 | Bhutan | BTN | 2019 | 1.867201 |
| 783 | Bhutan | BTN | 2018 | 1.908290 |
| 784 | Bhutan | BTN | 2017 | 1.731866 |
| 785 | Bhutan | BTN | 2016 | 1.638389 |
| 786 | Bhutan | BTN | 2015 | 1.402040 |
| 787 | Bhutan | BTN | 2014 | 1.374877 |
| 788 | Bhutan | BTN | 2013 | 1.245732 |
| 789 | Bhutan | BTN | 2012 | 1.156356 |
| 790 | Bhutan | BTN | 2011 | 1.043274 |
| 791 | Bhutan | BTN | 2010 | 0.699034 |
| 792 | Bolivia | BOL | 2020 | 1.539465 |
| 793 | Bolivia | BOL | 2019 | 1.853462 |
| 794 | Bolivia | BOL | 2018 | 1.885188 |
| 795 | Bolivia | BOL | 2017 | 1.891315 |
| 796 | Bolivia | BOL | 2016 | 1.893694 |
| 797 | Bolivia | BOL | 2015 | 1.803674 |
| 798 | Bolivia | BOL | 2014 | 1.784219 |
| 799 | Bolivia | BOL | 2013 | 1.686988 |
| 800 | Bolivia | BOL | 2012 | 1.604682 |
| 801 | Bolivia | BOL | 2011 | 1.538219 |
| 802 | Bolivia | BOL | 2010 | 1.438111 |
| 803 | Bosnia and Herzegovina | BIH | 2020 | 6.312306 |
| 804 | Bosnia and Herzegovina | BIH | 2019 | 6.285664 |
| 805 | Bosnia and Herzegovina | BIH | 2018 | 6.651454 |
| 806 | Bosnia and Herzegovina | BIH | 2017 | 6.596663 |
| 807 | Bosnia and Herzegovina | BIH | 2016 | 6.422491 |
| 808 | Bosnia and Herzegovina | BIH | 2015 | 5.569579 |
| 809 | Bosnia and Herzegovina | BIH | 2014 | 5.462455 |
| 810 | Bosnia and Herzegovina | BIH | 2013 | 6.039376 |
| 811 | Bosnia and Herzegovina | BIH | 2012 | 5.976583 |
| 812 | Bosnia and Herzegovina | BIH | 2011 | 6.341785 |
| 813 | Bosnia and Herzegovina | BIH | 2010 | 5.468911 |
| 814 | Botswana | BWA | 2020 | 2.263463 |
| 815 | Botswana | BWA | 2019 | 2.879663 |
| 816 | Botswana | BWA | 2018 | 3.288471 |
| 817 | Botswana | BWA | 2017 | 3.054955 |
| 818 | Botswana | BWA | 2016 | 2.818087 |
| 819 | Botswana | BWA | 2015 | 3.014836 |
| 820 | Botswana | BWA | 2014 | 3.091925 |
| 821 | Botswana | BWA | 2013 | 2.445133 |
| 822 | Botswana | BWA | 2012 | 1.569503 |
| 823 | Botswana | BWA | 2011 | 1.819714 |
| 824 | Botswana | BWA | 2010 | 1.611970 |
| 825 | Brazil | BRA | 2020 | 1.942523 |
| 826 | Brazil | BRA | 2019 | 2.050770 |
| 827 | Brazil | BRA | 2018 | 2.064261 |
| 828 | Brazil | BRA | 2017 | 2.185487 |
| 829 | Brazil | BRA | 2016 | 2.161260 |
| 830 | Brazil | BRA | 2015 | 2.365361 |
| 831 | Brazil | BRA | 2014 | 2.514592 |
| 832 | Brazil | BRA | 2013 | 2.413447 |
| 833 | Brazil | BRA | 2012 | 2.271418 |
| 834 | Brazil | BRA | 2011 | 2.110628 |
| 835 | Brazil | BRA | 2010 | 2.026606 |
| 836 | British Virgin Islands | VGB | 2020 | NaN |
| 837 | British Virgin Islands | VGB | 2019 | NaN |
| 838 | British Virgin Islands | VGB | 2018 | NaN |
| 839 | British Virgin Islands | VGB | 2017 | NaN |
| 840 | British Virgin Islands | VGB | 2016 | NaN |
| 841 | British Virgin Islands | VGB | 2015 | NaN |
| 842 | British Virgin Islands | VGB | 2014 | NaN |
| 843 | British Virgin Islands | VGB | 2013 | NaN |
| 844 | British Virgin Islands | VGB | 2012 | NaN |
| 845 | British Virgin Islands | VGB | 2011 | NaN |
| 846 | British Virgin Islands | VGB | 2010 | NaN |
| 847 | Brunei Darussalam | BRN | 2020 | 21.705812 |
| 848 | Brunei Darussalam | BRN | 2019 | 16.111933 |
| 849 | Brunei Darussalam | BRN | 2018 | 17.362310 |
| 850 | Brunei Darussalam | BRN | 2017 | 16.943078 |
| 851 | Brunei Darussalam | BRN | 2016 | 16.358212 |
| 852 | Brunei Darussalam | BRN | 2015 | 15.180679 |
| 853 | Brunei Darussalam | BRN | 2014 | 16.993155 |
| 854 | Brunei Darussalam | BRN | 2013 | 17.509752 |
| 855 | Brunei Darussalam | BRN | 2012 | 17.951032 |
| 856 | Brunei Darussalam | BRN | 2011 | 18.262990 |
| 857 | Brunei Darussalam | BRN | 2010 | 18.105658 |
| 858 | Bulgaria | BGR | 2020 | 4.923280 |
| 859 | Bulgaria | BGR | 2019 | 5.613710 |
| 860 | Bulgaria | BGR | 2018 | 5.821777 |
| 861 | Bulgaria | BGR | 2017 | 6.202011 |
| 862 | Bulgaria | BGR | 2016 | 5.834419 |
| 863 | Bulgaria | BGR | 2015 | 6.207378 |
| 864 | Bulgaria | BGR | 2014 | 5.821534 |
| 865 | Bulgaria | BGR | 2013 | 5.459060 |
| 866 | Bulgaria | BGR | 2012 | 6.162577 |
| 867 | Bulgaria | BGR | 2011 | 6.754952 |
| 868 | Bulgaria | BGR | 2010 | 6.049625 |
| 869 | Burkina Faso | BFA | 2020 | 0.253533 |
| 870 | Burkina Faso | BFA | 2019 | 0.269502 |
| 871 | Burkina Faso | BFA | 2018 | 0.252428 |
| 872 | Burkina Faso | BFA | 2017 | 0.233174 |
| 873 | Burkina Faso | BFA | 2016 | 0.207403 |
| 874 | Burkina Faso | BFA | 2015 | 0.203109 |
| 875 | Burkina Faso | BFA | 2014 | 0.164944 |
| 876 | Burkina Faso | BFA | 2013 | 0.167098 |
| 877 | Burkina Faso | BFA | 2012 | 0.157359 |
| 878 | Burkina Faso | BFA | 2011 | 0.132533 |
| 879 | Burkina Faso | BFA | 2010 | 0.129945 |
| 880 | Burundi | BDI | 2020 | 0.058384 |
| 881 | Burundi | BDI | 2019 | 0.059571 |
| 882 | Burundi | BDI | 2018 | 0.057850 |
| 883 | Burundi | BDI | 2017 | 0.047429 |
| 884 | Burundi | BDI | 2016 | 0.040538 |
| 885 | Burundi | BDI | 2015 | 0.034194 |
| 886 | Burundi | BDI | 2014 | 0.034760 |
| 887 | Burundi | BDI | 2013 | 0.036100 |
| 888 | Burundi | BDI | 2012 | 0.037180 |
| 889 | Burundi | BDI | 2011 | 0.037998 |
| 890 | Burundi | BDI | 2010 | 0.035424 |
| 891 | Cabo Verde | CPV | 2020 | 1.065152 |
| 892 | Cabo Verde | CPV | 2019 | 1.069615 |
| 893 | Cabo Verde | CPV | 2018 | 1.041138 |
| 894 | Cabo Verde | CPV | 2017 | 1.034952 |
| 895 | Cabo Verde | CPV | 2016 | 0.972253 |
| 896 | Cabo Verde | CPV | 2015 | 0.905344 |
| 897 | Cabo Verde | CPV | 2014 | 0.909031 |
| 898 | Cabo Verde | CPV | 2013 | 0.929733 |
| 899 | Cabo Verde | CPV | 2012 | 0.984520 |
| 900 | Cabo Verde | CPV | 2011 | 1.074460 |
| 901 | Cabo Verde | CPV | 2010 | 1.037390 |
| 902 | Cambodia | KHM | 2020 | 1.137584 |
| 903 | Cambodia | KHM | 2019 | 1.116330 |
| 904 | Cambodia | KHM | 2018 | 0.845897 |
| 905 | Cambodia | KHM | 2017 | 0.799744 |
| 906 | Cambodia | KHM | 2016 | 0.708268 |
| 907 | Cambodia | KHM | 2015 | 0.546949 |
| 908 | Cambodia | KHM | 2014 | 0.456728 |
| 909 | Cambodia | KHM | 2013 | 0.382515 |
| 910 | Cambodia | KHM | 2012 | 0.383718 |
| 911 | Cambodia | KHM | 2011 | 0.368035 |
| 912 | Cambodia | KHM | 2010 | 0.357906 |
| 913 | Cameroon | CMR | 2020 | 0.374783 |
| 914 | Cameroon | CMR | 2019 | 0.370692 |
| 915 | Cameroon | CMR | 2018 | 0.388794 |
| 916 | Cameroon | CMR | 2017 | 0.372071 |
| 917 | Cameroon | CMR | 2016 | 0.378494 |
| 918 | Cameroon | CMR | 2015 | 0.369371 |
| 919 | Cameroon | CMR | 2014 | 0.368742 |
| 920 | Cameroon | CMR | 2013 | 0.347934 |
| 921 | Cameroon | CMR | 2012 | 0.326478 |
| 922 | Cameroon | CMR | 2011 | 0.332610 |
| 923 | Cameroon | CMR | 2010 | 0.352872 |
| 924 | Canada | CAN | 2020 | 13.599375 |
| 925 | Canada | CAN | 2019 | 15.052747 |
| 926 | Canada | CAN | 2018 | 15.636654 |
| 927 | Canada | CAN | 2017 | 15.547195 |
| 928 | Canada | CAN | 2016 | 15.421823 |
| 929 | Canada | CAN | 2015 | 15.649907 |
| 930 | Canada | CAN | 2014 | 15.852177 |
| 931 | Canada | CAN | 2013 | 15.840810 |
| 932 | Canada | CAN | 2012 | 15.736824 |
| 933 | Canada | CAN | 2011 | 15.998272 |
| 934 | Canada | CAN | 2010 | 15.794538 |
| 935 | Cayman Islands | CYM | 2020 | NaN |
| 936 | Cayman Islands | CYM | 2019 | NaN |
| 937 | Cayman Islands | CYM | 2018 | NaN |
| 938 | Cayman Islands | CYM | 2017 | NaN |
| 939 | Cayman Islands | CYM | 2016 | NaN |
| 940 | Cayman Islands | CYM | 2015 | NaN |
| 941 | Cayman Islands | CYM | 2014 | NaN |
| 942 | Cayman Islands | CYM | 2013 | NaN |
| 943 | Cayman Islands | CYM | 2012 | NaN |
| 944 | Cayman Islands | CYM | 2011 | NaN |
| 945 | Cayman Islands | CYM | 2010 | NaN |
| 946 | Central African Republic | CAF | 2020 | 0.044282 |
| 947 | Central African Republic | CAF | 2019 | 0.045188 |
| 948 | Central African Republic | CAF | 2018 | 0.044968 |
| 949 | Central African Republic | CAF | 2017 | 0.044509 |
| 950 | Central African Republic | CAF | 2016 | 0.042087 |
| 951 | Central African Republic | CAF | 2015 | 0.038263 |
| 952 | Central African Republic | CAF | 2014 | 0.027174 |
| 953 | Central African Republic | CAF | 2013 | 0.025112 |
| 954 | Central African Republic | CAF | 2012 | 0.041313 |
| 955 | Central African Republic | CAF | 2011 | 0.041040 |
| 956 | Central African Republic | CAF | 2010 | 0.037510 |
| 957 | Chad | TCD | 2020 | 0.094228 |
| 958 | Chad | TCD | 2019 | 0.098196 |
| 959 | Chad | TCD | 2018 | 0.099806 |
| 960 | Chad | TCD | 2017 | 0.098649 |
| 961 | Chad | TCD | 2016 | 0.100727 |
| 962 | Chad | TCD | 2015 | 0.104563 |
| 963 | Chad | TCD | 2014 | 0.108278 |
| 964 | Chad | TCD | 2013 | 0.112528 |
| 965 | Chad | TCD | 2012 | 0.096726 |
| 966 | Chad | TCD | 2011 | 0.081481 |
| 967 | Chad | TCD | 2010 | 0.100044 |
| 968 | Channel Islands | CHI | 2020 | NaN |
| 969 | Channel Islands | CHI | 2019 | NaN |
| 970 | Channel Islands | CHI | 2018 | NaN |
| 971 | Channel Islands | CHI | 2017 | NaN |
| 972 | Channel Islands | CHI | 2016 | NaN |
| 973 | Channel Islands | CHI | 2015 | NaN |
| 974 | Channel Islands | CHI | 2014 | NaN |
| 975 | Channel Islands | CHI | 2013 | NaN |
| 976 | Channel Islands | CHI | 2012 | NaN |
| 977 | Channel Islands | CHI | 2011 | NaN |
| 978 | Channel Islands | CHI | 2010 | NaN |
| 979 | Chile | CHL | 2020 | 4.395151 |
| 980 | Chile | CHL | 2019 | 4.827620 |
| 981 | Chile | CHL | 2018 | 4.629657 |
| 982 | Chile | CHL | 2017 | 4.743802 |
| 983 | Chile | CHL | 2016 | 4.783526 |
| 984 | Chile | CHL | 2015 | 4.603236 |
| 985 | Chile | CHL | 2014 | 4.328593 |
| 986 | Chile | CHL | 2013 | 4.740083 |
| 987 | Chile | CHL | 2012 | 4.521603 |
| 988 | Chile | CHL | 2011 | 4.452801 |
| 989 | Chile | CHL | 2010 | 4.101884 |
| 990 | China | CHN | 2020 | 7.756138 |
| 991 | China | CHN | 2019 | 7.645436 |
| 992 | China | CHN | 2018 | 7.533193 |
| 993 | China | CHN | 2017 | 7.226160 |
| 994 | China | CHN | 2016 | 7.105480 |
| 995 | China | CHN | 2015 | 7.145132 |
| 996 | China | CHN | 2014 | 7.304713 |
| 997 | China | CHN | 2013 | 7.320155 |
| 998 | China | CHN | 2012 | 7.045200 |
| 999 | China | CHN | 2011 | 6.901347 |
| 1000 | China | CHN | 2010 | 6.335420 |
| 1001 | Colombia | COL | 2020 | 1.552259 |
| 1002 | Colombia | COL | 2019 | 1.577820 |
| 1003 | Colombia | COL | 2018 | 1.610392 |
| 1004 | Colombia | COL | 2017 | 1.565075 |
| 1005 | Colombia | COL | 2016 | 1.753796 |
| 1006 | Colombia | COL | 2015 | 1.719390 |
| 1007 | Colombia | COL | 2014 | 1.715821 |
| 1008 | Colombia | COL | 2013 | 1.680988 |
| 1009 | Colombia | COL | 2012 | 1.533846 |
| 1010 | Colombia | COL | 2011 | 1.539898 |
| 1011 | Colombia | COL | 2010 | 1.431318 |
| 1012 | Comoros | COM | 2020 | 0.407112 |
| 1013 | Comoros | COM | 2019 | 0.412397 |
| 1014 | Comoros | COM | 2018 | 0.389920 |
| 1015 | Comoros | COM | 2017 | 0.366303 |
| 1016 | Comoros | COM | 2016 | 0.292000 |
| 1017 | Comoros | COM | 2015 | 0.254582 |
| 1018 | Comoros | COM | 2014 | 0.240550 |
| 1019 | Comoros | COM | 2013 | 0.274810 |
| 1020 | Comoros | COM | 2012 | 0.233875 |
| 1021 | Comoros | COM | 2011 | 0.223857 |
| 1022 | Comoros | COM | 2010 | 0.255783 |
| 1023 | Congo, Dem. Rep. | COD | 2020 | 0.032585 |
| 1024 | Congo, Dem. Rep. | COD | 2019 | 0.033715 |
| 1025 | Congo, Dem. Rep. | COD | 2018 | 0.032311 |
| 1026 | Congo, Dem. Rep. | COD | 2017 | 0.033755 |
| 1027 | Congo, Dem. Rep. | COD | 2016 | 0.029732 |
| 1028 | Congo, Dem. Rep. | COD | 2015 | 0.041082 |
| 1029 | Congo, Dem. Rep. | COD | 2014 | 0.067549 |
| 1030 | Congo, Dem. Rep. | COD | 2013 | 0.053900 |
| 1031 | Congo, Dem. Rep. | COD | 2012 | 0.039822 |
| 1032 | Congo, Dem. Rep. | COD | 2011 | 0.043943 |
| 1033 | Congo, Dem. Rep. | COD | 2010 | 0.039974 |
| 1034 | Congo, Rep. | COG | 2020 | 1.254592 |
| 1035 | Congo, Rep. | COG | 2019 | 1.257662 |
| 1036 | Congo, Rep. | COG | 2018 | 1.142589 |
| 1037 | Congo, Rep. | COG | 2017 | 1.017762 |
| 1038 | Congo, Rep. | COG | 2016 | 1.059916 |
| 1039 | Congo, Rep. | COG | 2015 | 1.116621 |
| 1040 | Congo, Rep. | COG | 2014 | 1.046561 |
| 1041 | Congo, Rep. | COG | 2013 | 1.100153 |
| 1042 | Congo, Rep. | COG | 2012 | 1.116160 |
| 1043 | Congo, Rep. | COG | 2011 | 1.174458 |
| 1044 | Congo, Rep. | COG | 2010 | 1.222058 |
| 1045 | Costa Rica | CRI | 2020 | 1.359996 |
| 1046 | Costa Rica | CRI | 2019 | 1.564824 |
| 1047 | Costa Rica | CRI | 2018 | 1.620121 |
| 1048 | Costa Rica | CRI | 2017 | 1.636716 |
| 1049 | Costa Rica | CRI | 2016 | 1.619528 |
| 1050 | Costa Rica | CRI | 2015 | 1.539842 |
| 1051 | Costa Rica | CRI | 2014 | 1.616811 |
| 1052 | Costa Rica | CRI | 2013 | 1.623425 |
| 1053 | Costa Rica | CRI | 2012 | 1.572164 |
| 1054 | Costa Rica | CRI | 2011 | 1.587803 |
| 1055 | Costa Rica | CRI | 2010 | 1.537238 |
| 1056 | Cote d'Ivoire | CIV | 2020 | 0.406347 |
| 1057 | Cote d'Ivoire | CIV | 2019 | 0.414528 |
| 1058 | Cote d'Ivoire | CIV | 2018 | 0.399890 |
| 1059 | Cote d'Ivoire | CIV | 2017 | 0.425137 |
| 1060 | Cote d'Ivoire | CIV | 2016 | 0.396203 |
| 1061 | Cote d'Ivoire | CIV | 2015 | 0.415553 |
| 1062 | Cote d'Ivoire | CIV | 2014 | 0.399943 |
| 1063 | Cote d'Ivoire | CIV | 2013 | 0.386857 |
| 1064 | Cote d'Ivoire | CIV | 2012 | 0.365172 |
| 1065 | Cote d'Ivoire | CIV | 2011 | 0.283742 |
| 1066 | Cote d'Ivoire | CIV | 2010 | 0.300691 |
| 1067 | Croatia | HRV | 2020 | 3.860705 |
| 1068 | Croatia | HRV | 2019 | 4.064519 |
| 1069 | Croatia | HRV | 2018 | 4.020066 |
| 1070 | Croatia | HRV | 2017 | 4.220577 |
| 1071 | Croatia | HRV | 2016 | 4.042978 |
| 1072 | Croatia | HRV | 2015 | 3.949539 |
| 1073 | Croatia | HRV | 2014 | 3.830795 |
| 1074 | Croatia | HRV | 2013 | 3.997144 |
| 1075 | Croatia | HRV | 2012 | 4.077976 |
| 1076 | Croatia | HRV | 2011 | 4.445055 |
| 1077 | Croatia | HRV | 2010 | 4.529771 |
| 1078 | Cuba | CUB | 2020 | 2.152770 |
| 1079 | Cuba | CUB | 2019 | 2.157741 |
| 1080 | Cuba | CUB | 2018 | 2.354699 |
| 1081 | Cuba | CUB | 2017 | 2.314781 |
| 1082 | Cuba | CUB | 2016 | 2.396083 |
| 1083 | Cuba | CUB | 2015 | 2.575844 |
| 1084 | Cuba | CUB | 2014 | 2.354133 |
| 1085 | Cuba | CUB | 2013 | 2.549971 |
| 1086 | Cuba | CUB | 2012 | 2.536932 |
| 1087 | Cuba | CUB | 2011 | 2.441544 |
| 1088 | Cuba | CUB | 2010 | 2.489722 |
| 1089 | Curacao | CUW | 2020 | NaN |
| 1090 | Curacao | CUW | 2019 | NaN |
| 1091 | Curacao | CUW | 2018 | NaN |
| 1092 | Curacao | CUW | 2017 | NaN |
| 1093 | Curacao | CUW | 2016 | NaN |
| 1094 | Curacao | CUW | 2015 | NaN |
| 1095 | Curacao | CUW | 2014 | NaN |
| 1096 | Curacao | CUW | 2013 | NaN |
| 1097 | Curacao | CUW | 2012 | NaN |
| 1098 | Curacao | CUW | 2011 | NaN |
| 1099 | Curacao | CUW | 2010 | NaN |
| 1100 | Cyprus | CYP | 2020 | 5.471998 |
| 1101 | Cyprus | CYP | 2019 | 5.851879 |
| 1102 | Cyprus | CYP | 2018 | 5.906151 |
| 1103 | Cyprus | CYP | 2017 | 6.091071 |
| 1104 | Cyprus | CYP | 2016 | 6.026642 |
| 1105 | Cyprus | CYP | 2015 | 5.771090 |
| 1106 | Cyprus | CYP | 2014 | 5.787450 |
| 1107 | Cyprus | CYP | 2013 | 5.508034 |
| 1108 | Cyprus | CYP | 2012 | 6.137878 |
| 1109 | Cyprus | CYP | 2011 | 6.667272 |
| 1110 | Cyprus | CYP | 2010 | 6.991677 |
| 1111 | Czechia | CZE | 2020 | 8.304017 |
| 1112 | Czechia | CZE | 2019 | 9.156118 |
| 1113 | Czechia | CZE | 2018 | 9.664628 |
| 1114 | Czechia | CZE | 2017 | 9.773987 |
| 1115 | Czechia | CZE | 2016 | 9.747754 |
| 1116 | Czechia | CZE | 2015 | 9.592920 |
| 1117 | Czechia | CZE | 2014 | 9.497131 |
| 1118 | Czechia | CZE | 2013 | 9.787677 |
| 1119 | Czechia | CZE | 2012 | 10.210484 |
| 1120 | Czechia | CZE | 2011 | 10.596338 |
| 1121 | Czechia | CZE | 2010 | 10.899669 |
| 1122 | Denmark | DNK | 2020 | 4.691237 |
| 1123 | Denmark | DNK | 2019 | 5.107386 |
| 1124 | Denmark | DNK | 2018 | 5.718913 |
| 1125 | Denmark | DNK | 2017 | 5.756134 |
| 1126 | Denmark | DNK | 2016 | 6.169734 |
| 1127 | Denmark | DNK | 2015 | 5.930325 |
| 1128 | Denmark | DNK | 2014 | 6.347153 |
| 1129 | Denmark | DNK | 2013 | 7.116863 |
| 1130 | Denmark | DNK | 2012 | 6.834608 |
| 1131 | Denmark | DNK | 2011 | 7.736728 |
| 1132 | Denmark | DNK | 2010 | 8.674757 |
| 1133 | Djibouti | DJI | 2020 | 0.392329 |
| 1134 | Djibouti | DJI | 2019 | 0.398764 |
| 1135 | Djibouti | DJI | 2018 | 0.392453 |
| 1136 | Djibouti | DJI | 2017 | 0.387798 |
| 1137 | Djibouti | DJI | 2016 | 0.386480 |
| 1138 | Djibouti | DJI | 2015 | 0.443772 |
| 1139 | Djibouti | DJI | 2014 | 0.406607 |
| 1140 | Djibouti | DJI | 2013 | 0.575033 |
| 1141 | Djibouti | DJI | 2012 | 0.516192 |
| 1142 | Djibouti | DJI | 2011 | 0.506933 |
| 1143 | Djibouti | DJI | 2010 | 0.564731 |
| 1144 | Dominica | DMA | 2020 | 2.261268 |
| 1145 | Dominica | DMA | 2019 | 2.437419 |
| 1146 | Dominica | DMA | 2018 | 2.333988 |
| 1147 | Dominica | DMA | 2017 | 2.352172 |
| 1148 | Dominica | DMA | 2016 | 2.604352 |
| 1149 | Dominica | DMA | 2015 | 2.584027 |
| 1150 | Dominica | DMA | 2014 | 2.594744 |
| 1151 | Dominica | DMA | 2013 | 2.490591 |
| 1152 | Dominica | DMA | 2012 | 2.424225 |
| 1153 | Dominica | DMA | 2011 | 2.212621 |
| 1154 | Dominica | DMA | 2010 | 2.508908 |
| 1155 | Dominican Republic | DOM | 2020 | 2.080182 |
| 1156 | Dominican Republic | DOM | 2019 | 2.368634 |
| 1157 | Dominican Republic | DOM | 2018 | 2.356224 |
| 1158 | Dominican Republic | DOM | 2017 | 2.211962 |
| 1159 | Dominican Republic | DOM | 2016 | 2.336099 |
| 1160 | Dominican Republic | DOM | 2015 | 2.267046 |
| 1161 | Dominican Republic | DOM | 2014 | 2.086215 |
| 1162 | Dominican Republic | DOM | 2013 | 2.095805 |
| 1163 | Dominican Republic | DOM | 2012 | 2.161475 |
| 1164 | Dominican Republic | DOM | 2011 | 2.111718 |
| 1165 | Dominican Republic | DOM | 2010 | 2.115519 |
| 1166 | Ecuador | ECU | 2020 | 1.957575 |
| 1167 | Ecuador | ECU | 2019 | 2.285055 |
| 1168 | Ecuador | ECU | 2018 | 2.366830 |
| 1169 | Ecuador | ECU | 2017 | 2.308764 |
| 1170 | Ecuador | ECU | 2016 | 2.420481 |
| 1171 | Ecuador | ECU | 2015 | 2.555603 |
| 1172 | Ecuador | ECU | 2014 | 2.619452 |
| 1173 | Ecuador | ECU | 2013 | 2.525035 |
| 1174 | Ecuador | ECU | 2012 | 2.395078 |
| 1175 | Ecuador | ECU | 2011 | 2.434523 |
| 1176 | Ecuador | ECU | 2010 | 2.485326 |
| 1177 | Egypt, Arab Rep. | EGY | 2020 | 1.961123 |
| 1178 | Egypt, Arab Rep. | EGY | 2019 | 2.063161 |
| 1179 | Egypt, Arab Rep. | EGY | 2018 | 2.294016 |
| 1180 | Egypt, Arab Rep. | EGY | 2017 | 2.402416 |
| 1181 | Egypt, Arab Rep. | EGY | 2016 | 2.359353 |
| 1182 | Egypt, Arab Rep. | EGY | 2015 | 2.315542 |
| 1183 | Egypt, Arab Rep. | EGY | 2014 | 2.292246 |
| 1184 | Egypt, Arab Rep. | EGY | 2013 | 2.290225 |
| 1185 | Egypt, Arab Rep. | EGY | 2012 | 2.356423 |
| 1186 | Egypt, Arab Rep. | EGY | 2011 | 2.306807 |
| 1187 | Egypt, Arab Rep. | EGY | 2010 | 2.295791 |
| 1188 | El Salvador | SLV | 2020 | 1.013280 |
| 1189 | El Salvador | SLV | 2019 | 1.259941 |
| 1190 | El Salvador | SLV | 2018 | 1.090587 |
| 1191 | El Salvador | SLV | 2017 | 1.012486 |
| 1192 | El Salvador | SLV | 2016 | 1.139923 |
| 1193 | El Salvador | SLV | 2015 | 1.123018 |
| 1194 | El Salvador | SLV | 2014 | 1.061627 |
| 1195 | El Salvador | SLV | 2013 | 1.043675 |
| 1196 | El Salvador | SLV | 2012 | 1.099056 |
| 1197 | El Salvador | SLV | 2011 | 1.104500 |
| 1198 | El Salvador | SLV | 2010 | 1.069539 |
| 1199 | Equatorial Guinea | GNQ | 2020 | 2.725731 |
| 1200 | Equatorial Guinea | GNQ | 2019 | 3.139989 |
| 1201 | Equatorial Guinea | GNQ | 2018 | 3.374296 |
| 1202 | Equatorial Guinea | GNQ | 2017 | 3.701194 |
| 1203 | Equatorial Guinea | GNQ | 2016 | 4.167551 |
| 1204 | Equatorial Guinea | GNQ | 2015 | 4.078924 |
| 1205 | Equatorial Guinea | GNQ | 2014 | 4.591320 |
| 1206 | Equatorial Guinea | GNQ | 2013 | 4.815341 |
| 1207 | Equatorial Guinea | GNQ | 2012 | 4.916826 |
| 1208 | Equatorial Guinea | GNQ | 2011 | 5.319906 |
| 1209 | Equatorial Guinea | GNQ | 2010 | 5.525507 |
| 1210 | Eritrea | ERI | 2020 | 0.198658 |
| 1211 | Eritrea | ERI | 2019 | 0.199267 |
| 1212 | Eritrea | ERI | 2018 | 0.196699 |
| 1213 | Eritrea | ERI | 2017 | 0.171175 |
| 1214 | Eritrea | ERI | 2016 | 0.172496 |
| 1215 | Eritrea | ERI | 2015 | 0.170928 |
| 1216 | Eritrea | ERI | 2014 | 0.178196 |
| 1217 | Eritrea | ERI | 2013 | 0.178812 |
| 1218 | Eritrea | ERI | 2012 | 0.192259 |
| 1219 | Eritrea | ERI | 2011 | 0.185776 |
| 1220 | Eritrea | ERI | 2010 | 0.159782 |
| 1221 | Estonia | EST | 2020 | 5.338400 |
| 1222 | Estonia | EST | 2019 | 7.582120 |
| 1223 | Estonia | EST | 2018 | 11.888936 |
| 1224 | Estonia | EST | 2017 | 12.732430 |
| 1225 | Estonia | EST | 2016 | 12.089467 |
| 1226 | Estonia | EST | 2015 | 10.929773 |
| 1227 | Estonia | EST | 2014 | 13.384783 |
| 1228 | Estonia | EST | 2013 | 14.299350 |
| 1229 | Estonia | EST | 2012 | 12.844221 |
| 1230 | Estonia | EST | 2011 | 13.938569 |
| 1231 | Estonia | EST | 2010 | 13.894666 |
| 1232 | Eswatini | SWZ | 2020 | 0.972088 |
| 1233 | Eswatini | SWZ | 2019 | 0.999903 |
| 1234 | Eswatini | SWZ | 2018 | 0.952924 |
| 1235 | Eswatini | SWZ | 2017 | 0.960404 |
| 1236 | Eswatini | SWZ | 2016 | 0.976785 |
| 1237 | Eswatini | SWZ | 2015 | 0.895906 |
| 1238 | Eswatini | SWZ | 2014 | 0.868133 |
| 1239 | Eswatini | SWZ | 2013 | 0.855749 |
| 1240 | Eswatini | SWZ | 2012 | 0.725453 |
| 1241 | Eswatini | SWZ | 2011 | 0.737219 |
| 1242 | Eswatini | SWZ | 2010 | 0.772056 |
| 1243 | Ethiopia | ETH | 2020 | 0.154432 |
| 1244 | Ethiopia | ETH | 2019 | 0.155169 |
| 1245 | Ethiopia | ETH | 2018 | 0.153230 |
| 1246 | Ethiopia | ETH | 2017 | 0.146790 |
| 1247 | Ethiopia | ETH | 2016 | 0.144807 |
| 1248 | Ethiopia | ETH | 2015 | 0.127316 |
| 1249 | Ethiopia | ETH | 2014 | 0.125220 |
| 1250 | Ethiopia | ETH | 2013 | 0.104968 |
| 1251 | Ethiopia | ETH | 2012 | 0.090618 |
| 1252 | Ethiopia | ETH | 2011 | 0.082244 |
| 1253 | Ethiopia | ETH | 2010 | 0.072539 |
| 1254 | Faroe Islands | FRO | 2020 | NaN |
| 1255 | Faroe Islands | FRO | 2019 | NaN |
| 1256 | Faroe Islands | FRO | 2018 | NaN |
| 1257 | Faroe Islands | FRO | 2017 | NaN |
| 1258 | Faroe Islands | FRO | 2016 | NaN |
| 1259 | Faroe Islands | FRO | 2015 | NaN |
| 1260 | Faroe Islands | FRO | 2014 | NaN |
| 1261 | Faroe Islands | FRO | 2013 | NaN |
| 1262 | Faroe Islands | FRO | 2012 | NaN |
| 1263 | Faroe Islands | FRO | 2011 | NaN |
| 1264 | Faroe Islands | FRO | 2010 | NaN |
| 1265 | Fiji | FJI | 2020 | 1.117096 |
| 1266 | Fiji | FJI | 2019 | 1.517205 |
| 1267 | Fiji | FJI | 2018 | 1.509473 |
| 1268 | Fiji | FJI | 2017 | 1.448392 |
| 1269 | Fiji | FJI | 2016 | 1.305137 |
| 1270 | Fiji | FJI | 2015 | 1.377889 |
| 1271 | Fiji | FJI | 2014 | 1.325528 |
| 1272 | Fiji | FJI | 2013 | 1.167986 |
| 1273 | Fiji | FJI | 2012 | 1.090489 |
| 1274 | Fiji | FJI | 2011 | 1.162321 |
| 1275 | Fiji | FJI | 2010 | 1.244298 |
| 1276 | Finland | FIN | 2020 | 6.570145 |
| 1277 | Finland | FIN | 2019 | 7.423040 |
| 1278 | Finland | FIN | 2018 | 8.049188 |
| 1279 | Finland | FIN | 2017 | 7.809319 |
| 1280 | Finland | FIN | 2016 | 8.316248 |
| 1281 | Finland | FIN | 2015 | 7.813698 |
| 1282 | Finland | FIN | 2014 | 8.452183 |
| 1283 | Finland | FIN | 2013 | 9.228086 |
| 1284 | Finland | FIN | 2012 | 9.126037 |
| 1285 | Finland | FIN | 2011 | 10.230256 |
| 1286 | Finland | FIN | 2010 | 11.658082 |
| 1287 | France | FRA | 2020 | 3.953682 |
| 1288 | France | FRA | 2019 | 4.460165 |
| 1289 | France | FRA | 2018 | 4.570517 |
| 1290 | France | FRA | 2017 | 4.747917 |
| 1291 | France | FRA | 2016 | 4.703476 |
| 1292 | France | FRA | 2015 | 4.675935 |
| 1293 | France | FRA | 2014 | 4.614807 |
| 1294 | France | FRA | 2013 | 5.127899 |
| 1295 | France | FRA | 2012 | 5.152358 |
| 1296 | France | FRA | 2011 | 5.127105 |
| 1297 | France | FRA | 2010 | 5.350408 |
| 1298 | French Polynesia | PYF | 2020 | NaN |
| 1299 | French Polynesia | PYF | 2019 | NaN |
| 1300 | French Polynesia | PYF | 2018 | NaN |
| 1301 | French Polynesia | PYF | 2017 | NaN |
| 1302 | French Polynesia | PYF | 2016 | NaN |
| 1303 | French Polynesia | PYF | 2015 | NaN |
| 1304 | French Polynesia | PYF | 2014 | NaN |
| 1305 | French Polynesia | PYF | 2013 | NaN |
| 1306 | French Polynesia | PYF | 2012 | NaN |
| 1307 | French Polynesia | PYF | 2011 | NaN |
| 1308 | French Polynesia | PYF | 2010 | NaN |
| 1309 | Gabon | GAB | 2020 | 2.333274 |
| 1310 | Gabon | GAB | 2019 | 2.351764 |
| 1311 | Gabon | GAB | 2018 | 2.335936 |
| 1312 | Gabon | GAB | 2017 | 2.497272 |
| 1313 | Gabon | GAB | 2016 | 3.059957 |
| 1314 | Gabon | GAB | 2015 | 3.014912 |
| 1315 | Gabon | GAB | 2014 | 3.031261 |
| 1316 | Gabon | GAB | 2013 | 3.043944 |
| 1317 | Gabon | GAB | 2012 | 3.050011 |
| 1318 | Gabon | GAB | 2011 | 3.259317 |
| 1319 | Gabon | GAB | 2010 | 3.367467 |
| 1320 | Gambia, The | GMB | 2020 | 0.237530 |
| 1321 | Gambia, The | GMB | 2019 | 0.241900 |
| 1322 | Gambia, The | GMB | 2018 | 0.244507 |
| 1323 | Gambia, The | GMB | 2017 | 0.252942 |
| 1324 | Gambia, The | GMB | 2016 | 0.255998 |
| 1325 | Gambia, The | GMB | 2015 | 0.260038 |
| 1326 | Gambia, The | GMB | 2014 | 0.231519 |
| 1327 | Gambia, The | GMB | 2013 | 0.202648 |
| 1328 | Gambia, The | GMB | 2012 | 0.219746 |
| 1329 | Gambia, The | GMB | 2011 | 0.223650 |
| 1330 | Gambia, The | GMB | 2010 | 0.224129 |
| 1331 | Georgia | GEO | 2020 | 2.754709 |
| 1332 | Georgia | GEO | 2019 | 2.835791 |
| 1333 | Georgia | GEO | 2018 | 2.609707 |
| 1334 | Georgia | GEO | 2017 | 2.657481 |
| 1335 | Georgia | GEO | 2016 | 2.632753 |
| 1336 | Georgia | GEO | 2015 | 2.523142 |
| 1337 | Georgia | GEO | 2014 | 2.326711 |
| 1338 | Georgia | GEO | 2013 | 2.158342 |
| 1339 | Georgia | GEO | 2012 | 1.929001 |
| 1340 | Georgia | GEO | 2011 | 1.736165 |
| 1341 | Georgia | GEO | 2010 | 1.405474 |
| 1342 | Germany | DEU | 2020 | 7.255221 |
| 1343 | Germany | DEU | 2019 | 7.927188 |
| 1344 | Germany | DEU | 2018 | 8.537043 |
| 1345 | Germany | DEU | 2017 | 8.858345 |
| 1346 | Germany | DEU | 2016 | 9.072972 |
| 1347 | Germany | DEU | 2015 | 9.087345 |
| 1348 | Germany | DEU | 2014 | 9.088528 |
| 1349 | Germany | DEU | 2013 | 9.624229 |
| 1350 | Germany | DEU | 2012 | 9.451289 |
| 1351 | Germany | DEU | 2011 | 9.299003 |
| 1352 | Germany | DEU | 2010 | 9.453389 |
| 1353 | Ghana | GHA | 2020 | 0.602887 |
| 1354 | Ghana | GHA | 2019 | 0.572265 |
| 1355 | Ghana | GHA | 2018 | 0.543393 |
| 1356 | Ghana | GHA | 2017 | 0.500790 |
| 1357 | Ghana | GHA | 2016 | 0.492155 |
| 1358 | Ghana | GHA | 2015 | 0.496025 |
| 1359 | Ghana | GHA | 2014 | 0.474058 |
| 1360 | Ghana | GHA | 2013 | 0.504974 |
| 1361 | Ghana | GHA | 2012 | 0.479415 |
| 1362 | Ghana | GHA | 2011 | 0.412239 |
| 1363 | Ghana | GHA | 2010 | 0.405971 |
| 1364 | Gibraltar | GIB | 2020 | NaN |
| 1365 | Gibraltar | GIB | 2019 | NaN |
| 1366 | Gibraltar | GIB | 2018 | NaN |
| 1367 | Gibraltar | GIB | 2017 | NaN |
| 1368 | Gibraltar | GIB | 2016 | NaN |
| 1369 | Gibraltar | GIB | 2015 | NaN |
| 1370 | Gibraltar | GIB | 2014 | NaN |
| 1371 | Gibraltar | GIB | 2013 | NaN |
| 1372 | Gibraltar | GIB | 2012 | NaN |
| 1373 | Gibraltar | GIB | 2011 | NaN |
| 1374 | Gibraltar | GIB | 2010 | NaN |
| 1375 | Greece | GRC | 2020 | 4.767185 |
| 1376 | Greece | GRC | 2019 | 5.595284 |
| 1377 | Greece | GRC | 2018 | 6.058131 |
| 1378 | Greece | GRC | 2017 | 6.210832 |
| 1379 | Greece | GRC | 2016 | 6.203487 |
| 1380 | Greece | GRC | 2015 | 6.285088 |
| 1381 | Greece | GRC | 2014 | 6.385059 |
| 1382 | Greece | GRC | 2013 | 6.610379 |
| 1383 | Greece | GRC | 2012 | 7.250812 |
| 1384 | Greece | GRC | 2011 | 7.613505 |
| 1385 | Greece | GRC | 2010 | 7.874815 |
| 1386 | Greenland | GRL | 2020 | NaN |
| 1387 | Greenland | GRL | 2019 | NaN |
| 1388 | Greenland | GRL | 2018 | NaN |
| 1389 | Greenland | GRL | 2017 | NaN |
| 1390 | Greenland | GRL | 2016 | NaN |
| 1391 | Greenland | GRL | 2015 | NaN |
| 1392 | Greenland | GRL | 2014 | NaN |
| 1393 | Greenland | GRL | 2013 | NaN |
| 1394 | Greenland | GRL | 2012 | NaN |
| 1395 | Greenland | GRL | 2011 | NaN |
| 1396 | Greenland | GRL | 2010 | NaN |
| 1397 | Grenada | GRD | 2020 | 2.624067 |
| 1398 | Grenada | GRD | 2019 | 2.820964 |
| 1399 | Grenada | GRD | 2018 | 2.628901 |
| 1400 | Grenada | GRD | 2017 | 2.377585 |
| 1401 | Grenada | GRD | 2016 | 2.312322 |
| 1402 | Grenada | GRD | 2015 | 2.291141 |
| 1403 | Grenada | GRD | 2014 | 2.148815 |
| 1404 | Grenada | GRD | 2013 | 2.711531 |
| 1405 | Grenada | GRD | 2012 | 2.403548 |
| 1406 | Grenada | GRD | 2011 | 2.265093 |
| 1407 | Grenada | GRD | 2010 | 2.399179 |
| 1408 | Guam | GUM | 2020 | NaN |
| 1409 | Guam | GUM | 2019 | NaN |
| 1410 | Guam | GUM | 2018 | NaN |
| 1411 | Guam | GUM | 2017 | NaN |
| 1412 | Guam | GUM | 2016 | NaN |
| 1413 | Guam | GUM | 2015 | NaN |
| 1414 | Guam | GUM | 2014 | NaN |
| 1415 | Guam | GUM | 2013 | NaN |
| 1416 | Guam | GUM | 2012 | NaN |
| 1417 | Guam | GUM | 2011 | NaN |
| 1418 | Guam | GUM | 2010 | NaN |
| 1419 | Guatemala | GTM | 2020 | 1.000407 |
| 1420 | Guatemala | GTM | 2019 | 1.145373 |
| 1421 | Guatemala | GTM | 2018 | 1.105754 |
| 1422 | Guatemala | GTM | 2017 | 1.027517 |
| 1423 | Guatemala | GTM | 2016 | 1.102618 |
| 1424 | Guatemala | GTM | 2015 | 1.057073 |
| 1425 | Guatemala | GTM | 2014 | 0.914557 |
| 1426 | Guatemala | GTM | 2013 | 0.867211 |
| 1427 | Guatemala | GTM | 2012 | 0.824229 |
| 1428 | Guatemala | GTM | 2011 | 0.810859 |
| 1429 | Guatemala | GTM | 2010 | 0.804898 |
| 1430 | Guinea | GIN | 2020 | 0.343646 |
| 1431 | Guinea | GIN | 2019 | 0.350766 |
| 1432 | Guinea | GIN | 2018 | 0.297494 |
| 1433 | Guinea | GIN | 2017 | 0.271355 |
| 1434 | Guinea | GIN | 2016 | 0.235228 |
| 1435 | Guinea | GIN | 2015 | 0.216953 |
| 1436 | Guinea | GIN | 2014 | 0.196385 |
| 1437 | Guinea | GIN | 2013 | 0.195379 |
| 1438 | Guinea | GIN | 2012 | 0.228832 |
| 1439 | Guinea | GIN | 2011 | 0.249028 |
| 1440 | Guinea | GIN | 2010 | 0.243683 |
| 1441 | Guinea-Bissau | GNB | 2020 | 0.163208 |
| 1442 | Guinea-Bissau | GNB | 2019 | 0.165089 |
| 1443 | Guinea-Bissau | GNB | 2018 | 0.165095 |
| 1444 | Guinea-Bissau | GNB | 2017 | 0.163100 |
| 1445 | Guinea-Bissau | GNB | 2016 | 0.166253 |
| 1446 | Guinea-Bissau | GNB | 2015 | 0.157581 |
| 1447 | Guinea-Bissau | GNB | 2014 | 0.151207 |
| 1448 | Guinea-Bissau | GNB | 2013 | 0.145722 |
| 1449 | Guinea-Bissau | GNB | 2012 | 0.148846 |
| 1450 | Guinea-Bissau | GNB | 2011 | 0.151335 |
| 1451 | Guinea-Bissau | GNB | 2010 | 0.153775 |
| 1452 | Guyana | GUY | 2020 | 3.472771 |
| 1453 | Guyana | GUY | 2019 | 3.500331 |
| 1454 | Guyana | GUY | 2018 | 3.293512 |
| 1455 | Guyana | GUY | 2017 | 3.241131 |
| 1456 | Guyana | GUY | 2016 | 3.265238 |
| 1457 | Guyana | GUY | 2015 | 2.754761 |
| 1458 | Guyana | GUY | 2014 | 2.747101 |
| 1459 | Guyana | GUY | 2013 | 2.643226 |
| 1460 | Guyana | GUY | 2012 | 2.689370 |
| 1461 | Guyana | GUY | 2011 | 2.461067 |
| 1462 | Guyana | GUY | 2010 | 2.352219 |
| 1463 | Haiti | HTI | 2020 | 0.283815 |
| 1464 | Haiti | HTI | 2019 | 0.297241 |
| 1465 | Haiti | HTI | 2018 | 0.298730 |
| 1466 | Haiti | HTI | 2017 | 0.306184 |
| 1467 | Haiti | HTI | 2016 | 0.314037 |
| 1468 | Haiti | HTI | 2015 | 0.310537 |
| 1469 | Haiti | HTI | 2014 | 0.290139 |
| 1470 | Haiti | HTI | 2013 | 0.258338 |
| 1471 | Haiti | HTI | 2012 | 0.238941 |
| 1472 | Haiti | HTI | 2011 | 0.270992 |
| 1473 | Haiti | HTI | 2010 | 0.249744 |
| 1474 | Honduras | HND | 2020 | 0.872911 |
| 1475 | Honduras | HND | 2019 | 1.023855 |
| 1476 | Honduras | HND | 2018 | 0.922234 |
| 1477 | Honduras | HND | 2017 | 0.974047 |
| 1478 | Honduras | HND | 2016 | 1.098713 |
| 1479 | Honduras | HND | 2015 | 1.133810 |
| 1480 | Honduras | HND | 2014 | 1.082851 |
| 1481 | Honduras | HND | 2013 | 1.080836 |
| 1482 | Honduras | HND | 2012 | 1.135690 |
| 1483 | Honduras | HND | 2011 | 1.098335 |
| 1484 | Honduras | HND | 2010 | 0.937979 |
| 1485 | Hong Kong SAR, China | HKG | 2020 | NaN |
| 1486 | Hong Kong SAR, China | HKG | 2019 | NaN |
| 1487 | Hong Kong SAR, China | HKG | 2018 | NaN |
| 1488 | Hong Kong SAR, China | HKG | 2017 | NaN |
| 1489 | Hong Kong SAR, China | HKG | 2016 | NaN |
| 1490 | Hong Kong SAR, China | HKG | 2015 | NaN |
| 1491 | Hong Kong SAR, China | HKG | 2014 | NaN |
| 1492 | Hong Kong SAR, China | HKG | 2013 | NaN |
| 1493 | Hong Kong SAR, China | HKG | 2012 | NaN |
| 1494 | Hong Kong SAR, China | HKG | 2011 | NaN |
| 1495 | Hong Kong SAR, China | HKG | 2010 | NaN |
| 1496 | Hungary | HUN | 2020 | 4.591653 |
| 1497 | Hungary | HUN | 2019 | 4.836876 |
| 1498 | Hungary | HUN | 2018 | 5.033254 |
| 1499 | Hungary | HUN | 2017 | 5.052102 |
| 1500 | Hungary | HUN | 2016 | 4.508691 |
| 1501 | Hungary | HUN | 2015 | 4.407597 |
| 1502 | Hungary | HUN | 2014 | 4.117502 |
| 1503 | Hungary | HUN | 2013 | 4.120314 |
| 1504 | Hungary | HUN | 2012 | 4.377582 |
| 1505 | Hungary | HUN | 2011 | 4.704030 |
| 1506 | Hungary | HUN | 2010 | 4.788039 |
| 1507 | Iceland | ISL | 2020 | 3.947465 |
| 1508 | Iceland | ISL | 2019 | 4.543450 |
| 1509 | Iceland | ISL | 2018 | 4.817689 |
| 1510 | Iceland | ISL | 2017 | 4.866045 |
| 1511 | Iceland | ISL | 2016 | 4.868247 |
| 1512 | Iceland | ISL | 2015 | 6.219488 |
| 1513 | Iceland | ISL | 2014 | 6.254085 |
| 1514 | Iceland | ISL | 2013 | 6.275559 |
| 1515 | Iceland | ISL | 2012 | 5.799212 |
| 1516 | Iceland | ISL | 2011 | 5.919333 |
| 1517 | Iceland | ISL | 2010 | 6.159973 |
| 1518 | India | IND | 2020 | 1.576093 |
| 1519 | India | IND | 2019 | 1.752534 |
| 1520 | India | IND | 2018 | 1.795595 |
| 1521 | India | IND | 2017 | 1.704927 |
| 1522 | India | IND | 2016 | 1.639914 |
| 1523 | India | IND | 2015 | 1.631323 |
| 1524 | India | IND | 2014 | 1.642465 |
| 1525 | India | IND | 2013 | 1.527674 |
| 1526 | India | IND | 2012 | 1.498204 |
| 1527 | India | IND | 2011 | 1.396878 |
| 1528 | India | IND | 2010 | 1.338034 |
| 1529 | Indonesia | IDN | 2020 | 2.071659 |
| 1530 | Indonesia | IDN | 2019 | 2.245286 |
| 1531 | Indonesia | IDN | 2018 | 2.126837 |
| 1532 | Indonesia | IDN | 2017 | 1.948574 |
| 1533 | Indonesia | IDN | 2016 | 1.848304 |
| 1534 | Indonesia | IDN | 2015 | 1.887564 |
| 1535 | Indonesia | IDN | 2014 | 1.891428 |
| 1536 | Indonesia | IDN | 2013 | 1.770402 |
| 1537 | Indonesia | IDN | 2012 | 1.925450 |
| 1538 | Indonesia | IDN | 2011 | 1.925542 |
| 1539 | Indonesia | IDN | 2010 | 1.702906 |
| 1540 | Iran, Islamic Rep. | IRN | 2020 | 7.063351 |
| 1541 | Iran, Islamic Rep. | IRN | 2019 | 7.222980 |
| 1542 | Iran, Islamic Rep. | IRN | 2018 | 7.445128 |
| 1543 | Iran, Islamic Rep. | IRN | 2017 | 7.412903 |
| 1544 | Iran, Islamic Rep. | IRN | 2016 | 7.288966 |
| 1545 | Iran, Islamic Rep. | IRN | 2015 | 7.325792 |
| 1546 | Iran, Islamic Rep. | IRN | 2014 | 7.570578 |
| 1547 | Iran, Islamic Rep. | IRN | 2013 | 7.439601 |
| 1548 | Iran, Islamic Rep. | IRN | 2012 | 7.230858 |
| 1549 | Iran, Islamic Rep. | IRN | 2011 | 7.231195 |
| 1550 | Iran, Islamic Rep. | IRN | 2010 | 7.179825 |
| 1551 | Iraq | IRQ | 2020 | 3.842178 |
| 1552 | Iraq | IRQ | 2019 | 4.347264 |
| 1553 | Iraq | IRQ | 2018 | 4.142680 |
| 1554 | Iraq | IRQ | 2017 | 3.948809 |
| 1555 | Iraq | IRQ | 2016 | 3.702551 |
| 1556 | Iraq | IRQ | 2015 | 3.526944 |
| 1557 | Iraq | IRQ | 2014 | 3.647856 |
| 1558 | Iraq | IRQ | 2013 | 3.920421 |
| 1559 | Iraq | IRQ | 2012 | 3.809432 |
| 1560 | Iraq | IRQ | 2011 | 3.491247 |
| 1561 | Iraq | IRQ | 2010 | 3.471957 |
| 1562 | Ireland | IRL | 2020 | 6.768228 |
| 1563 | Ireland | IRL | 2019 | 7.257749 |
| 1564 | Ireland | IRL | 2018 | 7.699028 |
| 1565 | Ireland | IRL | 2017 | 7.848150 |
| 1566 | Ireland | IRL | 2016 | 8.203376 |
| 1567 | Ireland | IRL | 2015 | 7.887609 |
| 1568 | Ireland | IRL | 2014 | 7.633852 |
| 1569 | Ireland | IRL | 2013 | 7.718343 |
| 1570 | Ireland | IRL | 2012 | 8.046360 |
| 1571 | Ireland | IRL | 2011 | 7.966688 |
| 1572 | Ireland | IRL | 2010 | 8.847879 |
| 1573 | Isle of Man | IMN | 2020 | NaN |
| 1574 | Isle of Man | IMN | 2019 | NaN |
| 1575 | Isle of Man | IMN | 2018 | NaN |
| 1576 | Isle of Man | IMN | 2017 | NaN |
| 1577 | Isle of Man | IMN | 2016 | NaN |
| 1578 | Isle of Man | IMN | 2015 | NaN |
| 1579 | Isle of Man | IMN | 2014 | NaN |
| 1580 | Isle of Man | IMN | 2013 | NaN |
| 1581 | Isle of Man | IMN | 2012 | NaN |
| 1582 | Isle of Man | IMN | 2011 | NaN |
| 1583 | Isle of Man | IMN | 2010 | NaN |
| 1584 | Israel | ISR | 2020 | 6.345216 |
| 1585 | Israel | ISR | 2019 | 6.935752 |
| 1586 | Israel | ISR | 2018 | 6.914993 |
| 1587 | Israel | ISR | 2017 | 7.563874 |
| 1588 | Israel | ISR | 2016 | 7.633162 |
| 1589 | Israel | ISR | 2015 | 7.913354 |
| 1590 | Israel | ISR | 2014 | 7.877332 |
| 1591 | Israel | ISR | 2013 | 8.313481 |
| 1592 | Israel | ISR | 2012 | 9.615473 |
| 1593 | Israel | ISR | 2011 | 8.991063 |
| 1594 | Israel | ISR | 2010 | 9.250262 |
| 1595 | Italy | ITA | 2020 | 4.732373 |
| 1596 | Italy | ITA | 2019 | 5.311031 |
| 1597 | Italy | ITA | 2018 | 5.376940 |
| 1598 | Italy | ITA | 2017 | 5.437912 |
| 1599 | Italy | ITA | 2016 | 5.498244 |
| 1600 | Italy | ITA | 2015 | 5.563294 |
| 1601 | Italy | ITA | 2014 | 5.387443 |
| 1602 | Italy | ITA | 2013 | 5.751878 |
| 1603 | Italy | ITA | 2012 | 6.327662 |
| 1604 | Italy | ITA | 2011 | 6.680550 |
| 1605 | Italy | ITA | 2010 | 6.836875 |
| 1606 | Jamaica | JAM | 2020 | 2.069042 |
| 1607 | Jamaica | JAM | 2019 | 2.983290 |
| 1608 | Jamaica | JAM | 2018 | 3.054589 |
| 1609 | Jamaica | JAM | 2017 | 2.572661 |
| 1610 | Jamaica | JAM | 2016 | 2.693657 |
| 1611 | Jamaica | JAM | 2015 | 2.536711 |
| 1612 | Jamaica | JAM | 2014 | 2.582578 |
| 1613 | Jamaica | JAM | 2013 | 2.669295 |
| 1614 | Jamaica | JAM | 2012 | 2.521544 |
| 1615 | Jamaica | JAM | 2011 | 2.741783 |
| 1616 | Jamaica | JAM | 2010 | 2.735949 |
| 1617 | Japan | JPN | 2020 | 8.031496 |
| 1618 | Japan | JPN | 2019 | 8.478401 |
| 1619 | Japan | JPN | 2018 | 8.761979 |
| 1620 | Japan | JPN | 2017 | 9.063691 |
| 1621 | Japan | JPN | 2016 | 9.166714 |
| 1622 | Japan | JPN | 2015 | 9.268050 |
| 1623 | Japan | JPN | 2014 | 9.564306 |
| 1624 | Japan | JPN | 2013 | 9.944495 |
| 1625 | Japan | JPN | 2012 | 9.827856 |
| 1626 | Japan | JPN | 2011 | 9.495010 |
| 1627 | Japan | JPN | 2010 | 9.036010 |
| 1628 | Jordan | JOR | 2020 | 1.919172 |
| 1629 | Jordan | JOR | 2019 | 2.163621 |
| 1630 | Jordan | JOR | 2018 | 2.362363 |
| 1631 | Jordan | JOR | 2017 | 2.547316 |
| 1632 | Jordan | JOR | 2016 | 2.481772 |
| 1633 | Jordan | JOR | 2015 | 2.665730 |
| 1634 | Jordan | JOR | 2014 | 2.951377 |
| 1635 | Jordan | JOR | 2013 | 3.093473 |
| 1636 | Jordan | JOR | 2012 | 3.344947 |
| 1637 | Jordan | JOR | 2011 | 2.919319 |
| 1638 | Jordan | JOR | 2010 | 2.913872 |
| 1639 | Kazakhstan | KAZ | 2020 | 11.297743 |
| 1640 | Kazakhstan | KAZ | 2019 | 11.050870 |
| 1641 | Kazakhstan | KAZ | 2018 | 11.867550 |
| 1642 | Kazakhstan | KAZ | 2017 | 11.913758 |
| 1643 | Kazakhstan | KAZ | 2016 | 11.378840 |
| 1644 | Kazakhstan | KAZ | 2015 | 10.891051 |
| 1645 | Kazakhstan | KAZ | 2014 | 12.104225 |
| 1646 | Kazakhstan | KAZ | 2013 | 15.263105 |
| 1647 | Kazakhstan | KAZ | 2012 | 14.566323 |
| 1648 | Kazakhstan | KAZ | 2011 | 14.824685 |
| 1649 | Kazakhstan | KAZ | 2010 | 14.073275 |
| 1650 | Kenya | KEN | 2020 | 0.374079 |
| 1651 | Kenya | KEN | 2019 | 0.382362 |
| 1652 | Kenya | KEN | 2018 | 0.385438 |
| 1653 | Kenya | KEN | 2017 | 0.410582 |
| 1654 | Kenya | KEN | 2016 | 0.403178 |
| 1655 | Kenya | KEN | 2015 | 0.386120 |
| 1656 | Kenya | KEN | 2014 | 0.364375 |
| 1657 | Kenya | KEN | 2013 | 0.321209 |
| 1658 | Kenya | KEN | 2012 | 0.296880 |
| 1659 | Kenya | KEN | 2011 | 0.327521 |
| 1660 | Kenya | KEN | 2010 | 0.323340 |
| 1661 | Kiribati | KIR | 2020 | 0.449934 |
| 1662 | Kiribati | KIR | 2019 | 0.592397 |
| 1663 | Kiribati | KIR | 2018 | 0.598719 |
| 1664 | Kiribati | KIR | 2017 | 0.604011 |
| 1665 | Kiribati | KIR | 2016 | 0.478429 |
| 1666 | Kiribati | KIR | 2015 | 0.520106 |
| 1667 | Kiribati | KIR | 2014 | 0.522677 |
| 1668 | Kiribati | KIR | 2013 | 0.563052 |
| 1669 | Kiribati | KIR | 2012 | 0.516942 |
| 1670 | Kiribati | KIR | 2011 | 0.493306 |
| 1671 | Kiribati | KIR | 2010 | 0.502801 |
| 1672 | Korea, Dem. People's Rep. | PRK | 2020 | 2.027149 |
| 1673 | Korea, Dem. People's Rep. | PRK | 2019 | 2.156764 |
| 1674 | Korea, Dem. People's Rep. | PRK | 2018 | 1.954950 |
| 1675 | Korea, Dem. People's Rep. | PRK | 2017 | 2.127501 |
| 1676 | Korea, Dem. People's Rep. | PRK | 2016 | 1.107843 |
| 1677 | Korea, Dem. People's Rep. | PRK | 2015 | 0.993803 |
| 1678 | Korea, Dem. People's Rep. | PRK | 2014 | 1.242662 |
| 1679 | Korea, Dem. People's Rep. | PRK | 2013 | 1.105084 |
| 1680 | Korea, Dem. People's Rep. | PRK | 2012 | 1.546278 |
| 1681 | Korea, Dem. People's Rep. | PRK | 2011 | 1.496902 |
| 1682 | Korea, Dem. People's Rep. | PRK | 2010 | 2.093854 |
| 1683 | Korea, Rep. | KOR | 2020 | 10.990030 |
| 1684 | Korea, Rep. | KOR | 2019 | 11.825284 |
| 1685 | Korea, Rep. | KOR | 2018 | 12.216456 |
| 1686 | Korea, Rep. | KOR | 2017 | 12.191493 |
| 1687 | Korea, Rep. | KOR | 2016 | 12.016205 |
| 1688 | Korea, Rep. | KOR | 2015 | 11.914686 |
| 1689 | Korea, Rep. | KOR | 2014 | 11.588716 |
| 1690 | Korea, Rep. | KOR | 2013 | 11.890037 |
| 1691 | Korea, Rep. | KOR | 2012 | 11.958527 |
| 1692 | Korea, Rep. | KOR | 2011 | 11.984804 |
| 1693 | Korea, Rep. | KOR | 2010 | 11.607830 |
| 1694 | Kosovo | XKX | 2020 | NaN |
| 1695 | Kosovo | XKX | 2019 | NaN |
| 1696 | Kosovo | XKX | 2018 | NaN |
| 1697 | Kosovo | XKX | 2017 | NaN |
| 1698 | Kosovo | XKX | 2016 | NaN |
| 1699 | Kosovo | XKX | 2015 | NaN |
| 1700 | Kosovo | XKX | 2014 | NaN |
| 1701 | Kosovo | XKX | 2013 | NaN |
| 1702 | Kosovo | XKX | 2012 | NaN |
| 1703 | Kosovo | XKX | 2011 | NaN |
| 1704 | Kosovo | XKX | 2010 | NaN |
| 1705 | Kuwait | KWT | 2020 | 21.169610 |
| 1706 | Kuwait | KWT | 2019 | 21.135214 |
| 1707 | Kuwait | KWT | 2018 | 21.461230 |
| 1708 | Kuwait | KWT | 2017 | 21.910401 |
| 1709 | Kuwait | KWT | 2016 | 22.572698 |
| 1710 | Kuwait | KWT | 2015 | 22.775020 |
| 1711 | Kuwait | KWT | 2014 | 22.749990 |
| 1712 | Kuwait | KWT | 2013 | 23.958143 |
| 1713 | Kuwait | KWT | 2012 | 25.132421 |
| 1714 | Kuwait | KWT | 2011 | 26.493555 |
| 1715 | Kuwait | KWT | 2010 | 27.426380 |
| 1716 | Kyrgyz Republic | KGZ | 2020 | 1.379975 |
| 1717 | Kyrgyz Republic | KGZ | 2019 | 1.551594 |
| 1718 | Kyrgyz Republic | KGZ | 2018 | 1.788258 |
| 1719 | Kyrgyz Republic | KGZ | 2017 | 1.522861 |
| 1720 | Kyrgyz Republic | KGZ | 2016 | 1.591512 |
| 1721 | Kyrgyz Republic | KGZ | 2015 | 1.723480 |
| 1722 | Kyrgyz Republic | KGZ | 2014 | 1.687687 |
| 1723 | Kyrgyz Republic | KGZ | 2013 | 1.653088 |
| 1724 | Kyrgyz Republic | KGZ | 2012 | 1.809459 |
| 1725 | Kyrgyz Republic | KGZ | 2011 | 1.394553 |
| 1726 | Kyrgyz Republic | KGZ | 2010 | 1.173737 |
| 1727 | Lao PDR | LAO | 2020 | 2.620283 |
| 1728 | Lao PDR | LAO | 2019 | 2.658175 |
| 1729 | Lao PDR | LAO | 2018 | 2.767598 |
| 1730 | Lao PDR | LAO | 2017 | 2.722882 |
| 1731 | Lao PDR | LAO | 2016 | 2.278533 |
| 1732 | Lao PDR | LAO | 2015 | 1.307699 |
| 1733 | Lao PDR | LAO | 2014 | 0.649261 |
| 1734 | Lao PDR | LAO | 2013 | 0.630353 |
| 1735 | Lao PDR | LAO | 2012 | 0.502688 |
| 1736 | Lao PDR | LAO | 2011 | 0.474259 |
| 1737 | Lao PDR | LAO | 2010 | 0.454991 |
| 1738 | Latvia | LVA | 2020 | 3.645612 |
| 1739 | Latvia | LVA | 2019 | 3.954966 |
| 1740 | Latvia | LVA | 2018 | 4.039698 |
| 1741 | Latvia | LVA | 2017 | 3.664156 |
| 1742 | Latvia | LVA | 2016 | 3.646423 |
| 1743 | Latvia | LVA | 2015 | 3.699520 |
| 1744 | Latvia | LVA | 2014 | 3.652506 |
| 1745 | Latvia | LVA | 2013 | 3.702785 |
| 1746 | Latvia | LVA | 2012 | 3.721491 |
| 1747 | Latvia | LVA | 2011 | 3.834182 |
| 1748 | Latvia | LVA | 2010 | 4.060966 |
| 1749 | Lebanon | LBN | 2020 | 3.792194 |
| 1750 | Lebanon | LBN | 2019 | 4.655298 |
| 1751 | Lebanon | LBN | 2018 | 4.604611 |
| 1752 | Lebanon | LBN | 2017 | 4.774873 |
| 1753 | Lebanon | LBN | 2016 | 4.434700 |
| 1754 | Lebanon | LBN | 2015 | 4.222074 |
| 1755 | Lebanon | LBN | 2014 | 4.008548 |
| 1756 | Lebanon | LBN | 2013 | 4.093170 |
| 1757 | Lebanon | LBN | 2012 | 4.532362 |
| 1758 | Lebanon | LBN | 2011 | 4.197198 |
| 1759 | Lebanon | LBN | 2010 | 4.176368 |
| 1760 | Lesotho | LSO | 2020 | 1.025642 |
| 1761 | Lesotho | LSO | 2019 | 1.033427 |
| 1762 | Lesotho | LSO | 2018 | 1.035752 |
| 1763 | Lesotho | LSO | 2017 | 1.106736 |
| 1764 | Lesotho | LSO | 2016 | 0.991757 |
| 1765 | Lesotho | LSO | 2015 | 1.012121 |
| 1766 | Lesotho | LSO | 2014 | 1.121112 |
| 1767 | Lesotho | LSO | 2013 | 1.063918 |
| 1768 | Lesotho | LSO | 2012 | 1.420925 |
| 1769 | Lesotho | LSO | 2011 | 1.415926 |
| 1770 | Lesotho | LSO | 2010 | 1.067262 |
| 1771 | Liberia | LBR | 2020 | 0.231839 |
| 1772 | Liberia | LBR | 2019 | 0.229916 |
| 1773 | Liberia | LBR | 2018 | 0.230417 |
| 1774 | Liberia | LBR | 2017 | 0.264436 |
| 1775 | Liberia | LBR | 2016 | 0.297038 |
| 1776 | Liberia | LBR | 2015 | 0.270536 |
| 1777 | Liberia | LBR | 2014 | 0.266651 |
| 1778 | Liberia | LBR | 2013 | 0.204460 |
| 1779 | Liberia | LBR | 2012 | 0.217961 |
| 1780 | Liberia | LBR | 2011 | 0.202858 |
| 1781 | Liberia | LBR | 2010 | 0.181534 |
| 1782 | Libya | LBY | 2020 | 6.682805 |
| 1783 | Libya | LBY | 2019 | 8.325768 |
| 1784 | Libya | LBY | 2018 | 8.351625 |
| 1785 | Libya | LBY | 2017 | 8.167602 |
| 1786 | Libya | LBY | 2016 | 7.751239 |
| 1787 | Libya | LBY | 2015 | 8.289608 |
| 1788 | Libya | LBY | 2014 | 9.723089 |
| 1789 | Libya | LBY | 2013 | 9.985813 |
| 1790 | Libya | LBY | 2012 | 9.934649 |
| 1791 | Libya | LBY | 2011 | 6.707420 |
| 1792 | Libya | LBY | 2010 | 9.174324 |
| 1793 | Liechtenstein | LIE | 2020 | 3.663848 |
| 1794 | Liechtenstein | LIE | 2019 | 3.872608 |
| 1795 | Liechtenstein | LIE | 2018 | 3.744019 |
| 1796 | Liechtenstein | LIE | 2017 | 4.111204 |
| 1797 | Liechtenstein | LIE | 2016 | 3.984106 |
| 1798 | Liechtenstein | LIE | 2015 | 4.277173 |
| 1799 | Liechtenstein | LIE | 2014 | 4.347077 |
| 1800 | Liechtenstein | LIE | 2013 | 5.231345 |
| 1801 | Liechtenstein | LIE | 2012 | 5.076714 |
| 1802 | Liechtenstein | LIE | 2011 | 4.884965 |
| 1803 | Liechtenstein | LIE | 2010 | 5.311764 |
| 1804 | Lithuania | LTU | 2020 | 4.184000 |
| 1805 | Lithuania | LTU | 2019 | 4.200152 |
| 1806 | Lithuania | LTU | 2018 | 4.159315 |
| 1807 | Lithuania | LTU | 2017 | 3.967681 |
| 1808 | Lithuania | LTU | 2016 | 3.905927 |
| 1809 | Lithuania | LTU | 2015 | 3.809894 |
| 1810 | Lithuania | LTU | 2014 | 3.704482 |
| 1811 | Lithuania | LTU | 2013 | 3.831065 |
| 1812 | Lithuania | LTU | 2012 | 3.991535 |
| 1813 | Lithuania | LTU | 2011 | 3.911873 |
| 1814 | Lithuania | LTU | 2010 | 4.069052 |
| 1815 | Luxembourg | LUX | 2020 | 12.456953 |
| 1816 | Luxembourg | LUX | 2019 | 15.323040 |
| 1817 | Luxembourg | LUX | 2018 | 15.331524 |
| 1818 | Luxembourg | LUX | 2017 | 15.103063 |
| 1819 | Luxembourg | LUX | 2016 | 15.198775 |
| 1820 | Luxembourg | LUX | 2015 | 16.034649 |
| 1821 | Luxembourg | LUX | 2014 | 17.333940 |
| 1822 | Luxembourg | LUX | 2013 | 18.722946 |
| 1823 | Luxembourg | LUX | 2012 | 20.148942 |
| 1824 | Luxembourg | LUX | 2011 | 21.041503 |
| 1825 | Luxembourg | LUX | 2010 | 21.755666 |
| 1826 | Macao SAR, China | MAC | 2020 | NaN |
| 1827 | Macao SAR, China | MAC | 2019 | NaN |
| 1828 | Macao SAR, China | MAC | 2018 | NaN |
| 1829 | Macao SAR, China | MAC | 2017 | NaN |
| 1830 | Macao SAR, China | MAC | 2016 | NaN |
| 1831 | Macao SAR, China | MAC | 2015 | NaN |
| 1832 | Macao SAR, China | MAC | 2014 | NaN |
| 1833 | Macao SAR, China | MAC | 2013 | NaN |
| 1834 | Macao SAR, China | MAC | 2012 | NaN |
| 1835 | Macao SAR, China | MAC | 2011 | NaN |
| 1836 | Macao SAR, China | MAC | 2010 | NaN |
| 1837 | Madagascar | MDG | 2020 | 0.097270 |
| 1838 | Madagascar | MDG | 2019 | 0.142654 |
| 1839 | Madagascar | MDG | 2018 | 0.123102 |
| 1840 | Madagascar | MDG | 2017 | 0.133017 |
| 1841 | Madagascar | MDG | 2016 | 0.124764 |
| 1842 | Madagascar | MDG | 2015 | 0.132173 |
| 1843 | Madagascar | MDG | 2014 | 0.124324 |
| 1844 | Madagascar | MDG | 2013 | 0.124225 |
| 1845 | Madagascar | MDG | 2012 | 0.119381 |
| 1846 | Madagascar | MDG | 2011 | 0.098169 |
| 1847 | Madagascar | MDG | 2010 | 0.086043 |
| 1848 | Malawi | MWI | 2020 | 0.084636 |
| 1849 | Malawi | MWI | 2019 | 0.087119 |
| 1850 | Malawi | MWI | 2018 | 0.087620 |
| 1851 | Malawi | MWI | 2017 | 0.077993 |
| 1852 | Malawi | MWI | 2016 | 0.070297 |
| 1853 | Malawi | MWI | 2015 | 0.064320 |
| 1854 | Malawi | MWI | 2014 | 0.063454 |
| 1855 | Malawi | MWI | 2013 | 0.072034 |
| 1856 | Malawi | MWI | 2012 | 0.069084 |
| 1857 | Malawi | MWI | 2011 | 0.070816 |
| 1858 | Malawi | MWI | 2010 | 0.066886 |
| 1859 | Malaysia | MYS | 2020 | 7.383715 |
| 1860 | Malaysia | MYS | 2019 | 7.465000 |
| 1861 | Malaysia | MYS | 2018 | 7.452371 |
| 1862 | Malaysia | MYS | 2017 | 7.039826 |
| 1863 | Malaysia | MYS | 2016 | 7.348421 |
| 1864 | Malaysia | MYS | 2015 | 7.603420 |
| 1865 | Malaysia | MYS | 2014 | 7.719436 |
| 1866 | Malaysia | MYS | 2013 | 7.402951 |
| 1867 | Malaysia | MYS | 2012 | 6.925635 |
| 1868 | Malaysia | MYS | 2011 | 6.935320 |
| 1869 | Malaysia | MYS | 2010 | 6.959707 |
| 1870 | Maldives | MDV | 2020 | 2.826385 |
| 1871 | Maldives | MDV | 2019 | 3.963267 |
| 1872 | Maldives | MDV | 2018 | 3.626485 |
| 1873 | Maldives | MDV | 2017 | 3.272571 |
| 1874 | Maldives | MDV | 2016 | 3.227063 |
| 1875 | Maldives | MDV | 2015 | 3.074737 |
| 1876 | Maldives | MDV | 2014 | 3.251923 |
| 1877 | Maldives | MDV | 2013 | 2.816125 |
| 1878 | Maldives | MDV | 2012 | 2.953509 |
| 1879 | Maldives | MDV | 2011 | 2.704839 |
| 1880 | Maldives | MDV | 2010 | 2.663348 |
| 1881 | Mali | MLI | 2020 | 0.195566 |
| 1882 | Mali | MLI | 2019 | 0.191439 |
| 1883 | Mali | MLI | 2018 | 0.194032 |
| 1884 | Mali | MLI | 2017 | 0.187962 |
| 1885 | Mali | MLI | 2016 | 0.182277 |
| 1886 | Mali | MLI | 2015 | 0.184609 |
| 1887 | Mali | MLI | 2014 | 0.180859 |
| 1888 | Mali | MLI | 2013 | 0.165467 |
| 1889 | Mali | MLI | 2012 | 0.152028 |
| 1890 | Mali | MLI | 2011 | 0.146305 |
| 1891 | Mali | MLI | 2010 | 0.138707 |
| 1892 | Malta | MLT | 2020 | 3.125558 |
| 1893 | Malta | MLT | 2019 | 3.290468 |
| 1894 | Malta | MLT | 2018 | 3.203475 |
| 1895 | Malta | MLT | 2017 | 3.250434 |
| 1896 | Malta | MLT | 2016 | 2.969764 |
| 1897 | Malta | MLT | 2015 | 3.723377 |
| 1898 | Malta | MLT | 2014 | 5.422291 |
| 1899 | Malta | MLT | 2013 | 5.567333 |
| 1900 | Malta | MLT | 2012 | 6.465283 |
| 1901 | Malta | MLT | 2011 | 6.181354 |
| 1902 | Malta | MLT | 2010 | 6.240169 |
| 1903 | Marshall Islands | MHL | 2020 | 2.533803 |
| 1904 | Marshall Islands | MHL | 2019 | 3.405026 |
| 1905 | Marshall Islands | MHL | 2018 | 3.285568 |
| 1906 | Marshall Islands | MHL | 2017 | 3.164007 |
| 1907 | Marshall Islands | MHL | 2016 | 3.031306 |
| 1908 | Marshall Islands | MHL | 2015 | 2.960939 |
| 1909 | Marshall Islands | MHL | 2014 | 2.858050 |
| 1910 | Marshall Islands | MHL | 2013 | 2.771070 |
| 1911 | Marshall Islands | MHL | 2012 | 2.662682 |
| 1912 | Marshall Islands | MHL | 2011 | 2.663722 |
| 1913 | Marshall Islands | MHL | 2010 | 2.635914 |
| 1914 | Mauritania | MRT | 2020 | 0.855176 |
| 1915 | Mauritania | MRT | 2019 | 0.872475 |
| 1916 | Mauritania | MRT | 2018 | 0.870136 |
| 1917 | Mauritania | MRT | 2017 | 0.819300 |
| 1918 | Mauritania | MRT | 2016 | 0.637776 |
| 1919 | Mauritania | MRT | 2015 | 0.751732 |
| 1920 | Mauritania | MRT | 2014 | 0.659481 |
| 1921 | Mauritania | MRT | 2013 | 0.561374 |
| 1922 | Mauritania | MRT | 2012 | 0.647780 |
| 1923 | Mauritania | MRT | 2011 | 0.619394 |
| 1924 | Mauritania | MRT | 2010 | 0.606441 |
| 1925 | Mauritius | MUS | 2020 | 2.938514 |
| 1926 | Mauritius | MUS | 2019 | 3.296801 |
| 1927 | Mauritius | MUS | 2018 | 3.266415 |
| 1928 | Mauritius | MUS | 2017 | 3.300216 |
| 1929 | Mauritius | MUS | 2016 | 3.193282 |
| 1930 | Mauritius | MUS | 2015 | 3.136405 |
| 1931 | Mauritius | MUS | 2014 | 3.131442 |
| 1932 | Mauritius | MUS | 2013 | 3.032741 |
| 1933 | Mauritius | MUS | 2012 | 2.966043 |
| 1934 | Mauritius | MUS | 2011 | 2.905612 |
| 1935 | Mauritius | MUS | 2010 | 2.928503 |
| 1936 | Mexico | MEX | 2020 | 3.040766 |
| 1937 | Mexico | MEX | 2019 | 3.612165 |
| 1938 | Mexico | MEX | 2018 | 3.587489 |
| 1939 | Mexico | MEX | 2017 | 3.862759 |
| 1940 | Mexico | MEX | 2016 | 3.920323 |
| 1941 | Mexico | MEX | 2015 | 3.925368 |
| 1942 | Mexico | MEX | 2014 | 3.892355 |
| 1943 | Mexico | MEX | 2013 | 4.056055 |
| 1944 | Mexico | MEX | 2012 | 4.202414 |
| 1945 | Mexico | MEX | 2011 | 4.190990 |
| 1946 | Mexico | MEX | 2010 | 4.113211 |
| 1947 | Micronesia, Fed. Sts. | FSM | 2020 | 0.958914 |
| 1948 | Micronesia, Fed. Sts. | FSM | 2019 | 1.330592 |
| 1949 | Micronesia, Fed. Sts. | FSM | 2018 | 1.332384 |
| 1950 | Micronesia, Fed. Sts. | FSM | 2017 | 1.328443 |
| 1951 | Micronesia, Fed. Sts. | FSM | 2016 | 1.338185 |
| 1952 | Micronesia, Fed. Sts. | FSM | 2015 | 1.323747 |
| 1953 | Micronesia, Fed. Sts. | FSM | 2014 | 1.293293 |
| 1954 | Micronesia, Fed. Sts. | FSM | 2013 | 1.275217 |
| 1955 | Micronesia, Fed. Sts. | FSM | 2012 | 1.223298 |
| 1956 | Micronesia, Fed. Sts. | FSM | 2011 | 1.105787 |
| 1957 | Micronesia, Fed. Sts. | FSM | 2010 | 0.977804 |
| 1958 | Moldova | MDA | 2020 | 3.267846 |
| 1959 | Moldova | MDA | 2019 | 3.348667 |
| 1960 | Moldova | MDA | 2018 | 3.160421 |
| 1961 | Moldova | MDA | 2017 | 2.926841 |
| 1962 | Moldova | MDA | 2016 | 2.904909 |
| 1963 | Moldova | MDA | 2015 | 2.828160 |
| 1964 | Moldova | MDA | 2014 | 2.698635 |
| 1965 | Moldova | MDA | 2013 | 2.511402 |
| 1966 | Moldova | MDA | 2012 | 2.844888 |
| 1967 | Moldova | MDA | 2011 | 2.916944 |
| 1968 | Moldova | MDA | 2010 | 2.897999 |
| 1969 | Monaco | MCO | 2020 | NaN |
| 1970 | Monaco | MCO | 2019 | NaN |
| 1971 | Monaco | MCO | 2018 | NaN |
| 1972 | Monaco | MCO | 2017 | NaN |
| 1973 | Monaco | MCO | 2016 | NaN |
| 1974 | Monaco | MCO | 2015 | NaN |
| 1975 | Monaco | MCO | 2014 | NaN |
| 1976 | Monaco | MCO | 2013 | NaN |
| 1977 | Monaco | MCO | 2012 | NaN |
| 1978 | Monaco | MCO | 2011 | NaN |
| 1979 | Monaco | MCO | 2010 | NaN |
| 1980 | Mongolia | MNG | 2020 | 6.430645 |
| 1981 | Mongolia | MNG | 2019 | 7.160836 |
| 1982 | Mongolia | MNG | 2018 | 6.809659 |
| 1983 | Mongolia | MNG | 2017 | 6.322775 |
| 1984 | Mongolia | MNG | 2016 | 5.998505 |
| 1985 | Mongolia | MNG | 2015 | 5.835435 |
| 1986 | Mongolia | MNG | 2014 | 6.242888 |
| 1987 | Mongolia | MNG | 2013 | 6.461561 |
| 1988 | Mongolia | MNG | 2012 | 6.138738 |
| 1989 | Mongolia | MNG | 2011 | 5.732418 |
| 1990 | Mongolia | MNG | 2010 | 5.295465 |
| 1991 | Montenegro | MNE | 2020 | 4.067561 |
| 1992 | Montenegro | MNE | 2019 | 4.181645 |
| 1993 | Montenegro | MNE | 2018 | 4.018308 |
| 1994 | Montenegro | MNE | 2017 | 3.642510 |
| 1995 | Montenegro | MNE | 2016 | 3.456033 |
| 1996 | Montenegro | MNE | 2015 | 3.791796 |
| 1997 | Montenegro | MNE | 2014 | 3.567649 |
| 1998 | Montenegro | MNE | 2013 | 3.649830 |
| 1999 | Montenegro | MNE | 2012 | 3.757003 |
| 2000 | Montenegro | MNE | 2011 | 4.089640 |
| 2001 | Montenegro | MNE | 2010 | 4.171913 |
| 2002 | Morocco | MAR | 2020 | 1.818526 |
| 2003 | Morocco | MAR | 2019 | 1.955308 |
| 2004 | Morocco | MAR | 2018 | 1.789328 |
| 2005 | Morocco | MAR | 2017 | 1.773663 |
| 2006 | Morocco | MAR | 2016 | 1.717306 |
| 2007 | Morocco | MAR | 2015 | 1.740534 |
| 2008 | Morocco | MAR | 2014 | 1.713696 |
| 2009 | Morocco | MAR | 2013 | 1.703831 |
| 2010 | Morocco | MAR | 2012 | 1.741296 |
| 2011 | Morocco | MAR | 2011 | 1.699611 |
| 2012 | Morocco | MAR | 2010 | 1.594016 |
| 2013 | Mozambique | MOZ | 2020 | 0.222768 |
| 2014 | Mozambique | MOZ | 2019 | 0.248640 |
| 2015 | Mozambique | MOZ | 2018 | 0.233657 |
| 2016 | Mozambique | MOZ | 2017 | 0.250698 |
| 2017 | Mozambique | MOZ | 2016 | 0.261542 |
| 2018 | Mozambique | MOZ | 2015 | 0.204085 |
| 2019 | Mozambique | MOZ | 2014 | 0.185236 |
| 2020 | Mozambique | MOZ | 2013 | 0.164365 |
| 2021 | Mozambique | MOZ | 2012 | 0.148679 |
| 2022 | Mozambique | MOZ | 2011 | 0.138647 |
| 2023 | Mozambique | MOZ | 2010 | 0.116175 |
| 2024 | Myanmar | MMR | 2020 | 0.634080 |
| 2025 | Myanmar | MMR | 2019 | 0.640929 |
| 2026 | Myanmar | MMR | 2018 | 0.622498 |
| 2027 | Myanmar | MMR | 2017 | 0.621496 |
| 2028 | Myanmar | MMR | 2016 | 0.421272 |
| 2029 | Myanmar | MMR | 2015 | 0.369707 |
| 2030 | Myanmar | MMR | 2014 | 0.333542 |
| 2031 | Myanmar | MMR | 2013 | 0.268370 |
| 2032 | Myanmar | MMR | 2012 | 0.238240 |
| 2033 | Myanmar | MMR | 2011 | 0.174575 |
| 2034 | Myanmar | MMR | 2010 | 0.164631 |
| 2035 | Namibia | NAM | 2020 | 1.588045 |
| 2036 | Namibia | NAM | 2019 | 1.764172 |
| 2037 | Namibia | NAM | 2018 | 1.778832 |
| 2038 | Namibia | NAM | 2017 | 1.786399 |
| 2039 | Namibia | NAM | 2016 | 1.787073 |
| 2040 | Namibia | NAM | 2015 | 1.812456 |
| 2041 | Namibia | NAM | 2014 | 1.753053 |
| 2042 | Namibia | NAM | 2013 | 1.706683 |
| 2043 | Namibia | NAM | 2012 | 1.618200 |
| 2044 | Namibia | NAM | 2011 | 1.549378 |
| 2045 | Namibia | NAM | 2010 | 1.478370 |
| 2046 | Nauru | NRU | 2020 | 3.361754 |
| 2047 | Nauru | NRU | 2019 | 4.401583 |
| 2048 | Nauru | NRU | 2018 | 4.528682 |
| 2049 | Nauru | NRU | 2017 | 4.793700 |
| 2050 | Nauru | NRU | 2016 | 4.607852 |
| 2051 | Nauru | NRU | 2015 | 4.872597 |
| 2052 | Nauru | NRU | 2014 | 4.625229 |
| 2053 | Nauru | NRU | 2013 | 4.423041 |
| 2054 | Nauru | NRU | 2012 | 4.031023 |
| 2055 | Nauru | NRU | 2011 | 3.899640 |
| 2056 | Nauru | NRU | 2010 | 4.169515 |
| 2057 | Nepal | NPL | 2020 | 0.509366 |
| 2058 | Nepal | NPL | 2019 | 0.480725 |
| 2059 | Nepal | NPL | 2018 | 0.531082 |
| 2060 | Nepal | NPL | 2017 | 0.470677 |
| 2061 | Nepal | NPL | 2016 | 0.385328 |
| 2062 | Nepal | NPL | 2015 | 0.260272 |
| 2063 | Nepal | NPL | 2014 | 0.259711 |
| 2064 | Nepal | NPL | 2013 | 0.222332 |
| 2065 | Nepal | NPL | 2012 | 0.219453 |
| 2066 | Nepal | NPL | 2011 | 0.190682 |
| 2067 | Nepal | NPL | 2010 | 0.170863 |
| 2068 | Netherlands | NLD | 2020 | 7.471553 |
| 2069 | Netherlands | NLD | 2019 | 8.413969 |
| 2070 | Netherlands | NLD | 2018 | 8.785144 |
| 2071 | Netherlands | NLD | 2017 | 9.089266 |
| 2072 | Netherlands | NLD | 2016 | 9.306892 |
| 2073 | Netherlands | NLD | 2015 | 9.290243 |
| 2074 | Netherlands | NLD | 2014 | 8.881905 |
| 2075 | Netherlands | NLD | 2013 | 9.348141 |
| 2076 | Netherlands | NLD | 2012 | 9.398613 |
| 2077 | Netherlands | NLD | 2011 | 9.511010 |
| 2078 | Netherlands | NLD | 2010 | 10.298311 |
| 2079 | New Caledonia | NCL | 2020 | NaN |
| 2080 | New Caledonia | NCL | 2019 | NaN |
| 2081 | New Caledonia | NCL | 2018 | NaN |
| 2082 | New Caledonia | NCL | 2017 | NaN |
| 2083 | New Caledonia | NCL | 2016 | NaN |
| 2084 | New Caledonia | NCL | 2015 | NaN |
| 2085 | New Caledonia | NCL | 2014 | NaN |
| 2086 | New Caledonia | NCL | 2013 | NaN |
| 2087 | New Caledonia | NCL | 2012 | NaN |
| 2088 | New Caledonia | NCL | 2011 | NaN |
| 2089 | New Caledonia | NCL | 2010 | NaN |
| 2090 | New Zealand | NZL | 2020 | 6.160799 |
| 2091 | New Zealand | NZL | 2019 | 6.830053 |
| 2092 | New Zealand | NZL | 2018 | 6.613272 |
| 2093 | New Zealand | NZL | 2017 | 6.840494 |
| 2094 | New Zealand | NZL | 2016 | 6.615409 |
| 2095 | New Zealand | NZL | 2015 | 7.003341 |
| 2096 | New Zealand | NZL | 2014 | 7.078645 |
| 2097 | New Zealand | NZL | 2013 | 7.178024 |
| 2098 | New Zealand | NZL | 2012 | 7.283728 |
| 2099 | New Zealand | NZL | 2011 | 6.909352 |
| 2100 | New Zealand | NZL | 2010 | 7.136622 |
| 2101 | Nicaragua | NIC | 2020 | 0.678252 |
| 2102 | Nicaragua | NIC | 2019 | 0.770102 |
| 2103 | Nicaragua | NIC | 2018 | 0.764550 |
| 2104 | Nicaragua | NIC | 2017 | 0.837724 |
| 2105 | Nicaragua | NIC | 2016 | 0.846846 |
| 2106 | Nicaragua | NIC | 2015 | 0.839346 |
| 2107 | Nicaragua | NIC | 2014 | 0.766444 |
| 2108 | Nicaragua | NIC | 2013 | 0.731006 |
| 2109 | Nicaragua | NIC | 2012 | 0.777036 |
| 2110 | Nicaragua | NIC | 2011 | 0.802046 |
| 2111 | Nicaragua | NIC | 2010 | 0.770732 |
| 2112 | Niger | NER | 2020 | 0.090326 |
| 2113 | Niger | NER | 2019 | 0.092101 |
| 2114 | Niger | NER | 2018 | 0.086649 |
| 2115 | Niger | NER | 2017 | 0.087451 |
| 2116 | Niger | NER | 2016 | 0.100195 |
| 2117 | Niger | NER | 2015 | 0.104907 |
| 2118 | Niger | NER | 2014 | 0.111335 |
| 2119 | Niger | NER | 2013 | 0.105880 |
| 2120 | Niger | NER | 2012 | 0.105020 |
| 2121 | Niger | NER | 2011 | 0.080972 |
| 2122 | Niger | NER | 2010 | 0.081757 |
| 2123 | Nigeria | NGA | 2020 | 0.537510 |
| 2124 | Nigeria | NGA | 2019 | 0.588005 |
| 2125 | Nigeria | NGA | 2018 | 0.572783 |
| 2126 | Nigeria | NGA | 2017 | 0.560638 |
| 2127 | Nigeria | NGA | 2016 | 0.587371 |
| 2128 | Nigeria | NGA | 2015 | 0.585592 |
| 2129 | Nigeria | NGA | 2014 | 0.640072 |
| 2130 | Nigeria | NGA | 2013 | 0.618779 |
| 2131 | Nigeria | NGA | 2012 | 0.560546 |
| 2132 | Nigeria | NGA | 2011 | 0.574123 |
| 2133 | Nigeria | NGA | 2010 | 0.559513 |
| 2134 | North Macedonia | MKD | 2020 | 3.279420 |
| 2135 | North Macedonia | MKD | 2019 | 3.831137 |
| 2136 | North Macedonia | MKD | 2018 | 3.347723 |
| 2137 | North Macedonia | MKD | 2017 | 3.584571 |
| 2138 | North Macedonia | MKD | 2016 | 3.359582 |
| 2139 | North Macedonia | MKD | 2015 | 3.449913 |
| 2140 | North Macedonia | MKD | 2014 | 3.600002 |
| 2141 | North Macedonia | MKD | 2013 | 3.809146 |
| 2142 | North Macedonia | MKD | 2012 | 4.269147 |
| 2143 | North Macedonia | MKD | 2011 | 4.448349 |
| 2144 | North Macedonia | MKD | 2010 | 4.053325 |
| 2145 | Northern Mariana Islands | MNP | 2020 | NaN |
| 2146 | Northern Mariana Islands | MNP | 2019 | NaN |
| 2147 | Northern Mariana Islands | MNP | 2018 | NaN |
| 2148 | Northern Mariana Islands | MNP | 2017 | NaN |
| 2149 | Northern Mariana Islands | MNP | 2016 | NaN |
| 2150 | Northern Mariana Islands | MNP | 2015 | NaN |
| 2151 | Northern Mariana Islands | MNP | 2014 | NaN |
| 2152 | Northern Mariana Islands | MNP | 2013 | NaN |
| 2153 | Northern Mariana Islands | MNP | 2012 | NaN |
| 2154 | Northern Mariana Islands | MNP | 2011 | NaN |
| 2155 | Northern Mariana Islands | MNP | 2010 | NaN |
| 2156 | Norway | NOR | 2020 | 6.725080 |
| 2157 | Norway | NOR | 2019 | 7.042321 |
| 2158 | Norway | NOR | 2018 | 7.261316 |
| 2159 | Norway | NOR | 2017 | 7.423752 |
| 2160 | Norway | NOR | 2016 | 7.561039 |
| 2161 | Norway | NOR | 2015 | 7.764859 |
| 2162 | Norway | NOR | 2014 | 7.716802 |
| 2163 | Norway | NOR | 2013 | 7.801169 |
| 2164 | Norway | NOR | 2012 | 7.725324 |
| 2165 | Norway | NOR | 2011 | 7.888271 |
| 2166 | Norway | NOR | 2010 | 8.205018 |
| 2167 | Oman | OMN | 2020 | 15.636201 |
| 2168 | Oman | OMN | 2019 | 16.456358 |
| 2169 | Oman | OMN | 2018 | 16.379576 |
| 2170 | Oman | OMN | 2017 | 15.771797 |
| 2171 | Oman | OMN | 2016 | 16.415746 |
| 2172 | Oman | OMN | 2015 | 16.730784 |
| 2173 | Oman | OMN | 2014 | 16.558314 |
| 2174 | Oman | OMN | 2013 | 16.510527 |
| 2175 | Oman | OMN | 2012 | 17.125738 |
| 2176 | Oman | OMN | 2011 | 16.720416 |
| 2177 | Oman | OMN | 2010 | 16.335081 |
| 2178 | Pakistan | PAK | 2020 | 0.810360 |
| 2179 | Pakistan | PAK | 2019 | 0.824460 |
| 2180 | Pakistan | PAK | 2018 | 0.850427 |
| 2181 | Pakistan | PAK | 2017 | 0.918473 |
| 2182 | Pakistan | PAK | 2016 | 0.848207 |
| 2183 | Pakistan | PAK | 2015 | 0.778086 |
| 2184 | Pakistan | PAK | 2014 | 0.740619 |
| 2185 | Pakistan | PAK | 2013 | 0.710994 |
| 2186 | Pakistan | PAK | 2012 | 0.711251 |
| 2187 | Pakistan | PAK | 2011 | 0.713434 |
| 2188 | Pakistan | PAK | 2010 | 0.721910 |
| 2189 | Palau | PLW | 2020 | 8.802582 |
| 2190 | Palau | PLW | 2019 | 12.134405 |
| 2191 | Palau | PLW | 2018 | 11.861845 |
| 2192 | Palau | PLW | 2017 | 11.941470 |
| 2193 | Palau | PLW | 2016 | 11.669286 |
| 2194 | Palau | PLW | 2015 | 11.290323 |
| 2195 | Palau | PLW | 2014 | 12.238705 |
| 2196 | Palau | PLW | 2013 | 12.417860 |
| 2197 | Palau | PLW | 2012 | 12.370445 |
| 2198 | Palau | PLW | 2011 | 11.655702 |
| 2199 | Palau | PLW | 2010 | 11.585761 |
| 2200 | Panama | PAN | 2020 | 2.231443 |
| 2201 | Panama | PAN | 2019 | 3.095050 |
| 2202 | Panama | PAN | 2018 | 2.381319 |
| 2203 | Panama | PAN | 2017 | 2.474669 |
| 2204 | Panama | PAN | 2016 | 2.645681 |
| 2205 | Panama | PAN | 2015 | 2.681232 |
| 2206 | Panama | PAN | 2014 | 2.766437 |
| 2207 | Panama | PAN | 2013 | 2.682755 |
| 2208 | Panama | PAN | 2012 | 2.786148 |
| 2209 | Panama | PAN | 2011 | 2.709402 |
| 2210 | Panama | PAN | 2010 | 2.536306 |
| 2211 | Papua New Guinea | PNG | 2020 | 0.563252 |
| 2212 | Papua New Guinea | PNG | 2019 | 0.782553 |
| 2213 | Papua New Guinea | PNG | 2018 | 0.762550 |
| 2214 | Papua New Guinea | PNG | 2017 | 0.713598 |
| 2215 | Papua New Guinea | PNG | 2016 | 0.737249 |
| 2216 | Papua New Guinea | PNG | 2015 | 0.733653 |
| 2217 | Papua New Guinea | PNG | 2014 | 0.689602 |
| 2218 | Papua New Guinea | PNG | 2013 | 0.633609 |
| 2219 | Papua New Guinea | PNG | 2012 | 0.611185 |
| 2220 | Papua New Guinea | PNG | 2011 | 0.663474 |
| 2221 | Papua New Guinea | PNG | 2010 | 0.664885 |
| 2222 | Paraguay | PRY | 2020 | 1.144591 |
| 2223 | Paraguay | PRY | 2019 | 1.240669 |
| 2224 | Paraguay | PRY | 2018 | 1.297482 |
| 2225 | Paraguay | PRY | 2017 | 1.246325 |
| 2226 | Paraguay | PRY | 2016 | 1.147765 |
| 2227 | Paraguay | PRY | 2015 | 1.030682 |
| 2228 | Paraguay | PRY | 2014 | 0.924029 |
| 2229 | Paraguay | PRY | 2013 | 0.882702 |
| 2230 | Paraguay | PRY | 2012 | 0.874070 |
| 2231 | Paraguay | PRY | 2011 | 0.892891 |
| 2232 | Paraguay | PRY | 2010 | 0.874266 |
| 2233 | Peru | PER | 2020 | 1.398566 |
| 2234 | Peru | PER | 2019 | 1.735642 |
| 2235 | Peru | PER | 2018 | 1.695131 |
| 2236 | Peru | PER | 2017 | 1.717243 |
| 2237 | Peru | PER | 2016 | 1.826380 |
| 2238 | Peru | PER | 2015 | 1.776301 |
| 2239 | Peru | PER | 2014 | 1.751594 |
| 2240 | Peru | PER | 2013 | 1.656254 |
| 2241 | Peru | PER | 2012 | 1.617522 |
| 2242 | Peru | PER | 2011 | 1.642847 |
| 2243 | Peru | PER | 2010 | 1.539485 |
| 2244 | Philippines | PHL | 2020 | 1.189679 |
| 2245 | Philippines | PHL | 2019 | 1.321528 |
| 2246 | Philippines | PHL | 2018 | 1.281391 |
| 2247 | Philippines | PHL | 2017 | 1.250315 |
| 2248 | Philippines | PHL | 2016 | 1.152751 |
| 2249 | Philippines | PHL | 2015 | 1.077254 |
| 2250 | Philippines | PHL | 2014 | 1.004908 |
| 2251 | Philippines | PHL | 2013 | 0.957914 |
| 2252 | Philippines | PHL | 2012 | 0.878945 |
| 2253 | Philippines | PHL | 2011 | 0.856823 |
| 2254 | Philippines | PHL | 2010 | 0.865603 |
| 2255 | Poland | POL | 2020 | 7.367563 |
| 2256 | Poland | POL | 2019 | 7.768856 |
| 2257 | Poland | POL | 2018 | 8.209531 |
| 2258 | Poland | POL | 2017 | 8.236243 |
| 2259 | Poland | POL | 2016 | 7.895752 |
| 2260 | Poland | POL | 2015 | 7.610021 |
| 2261 | Poland | POL | 2014 | 7.516889 |
| 2262 | Poland | POL | 2013 | 7.841821 |
| 2263 | Poland | POL | 2012 | 7.969684 |
| 2264 | Poland | POL | 2011 | 8.159933 |
| 2265 | Poland | POL | 2010 | 8.247005 |
| 2266 | Portugal | PRT | 2020 | 3.784908 |
| 2267 | Portugal | PRT | 2019 | 4.332448 |
| 2268 | Portugal | PRT | 2018 | 4.809613 |
| 2269 | Portugal | PRT | 2017 | 5.171956 |
| 2270 | Portugal | PRT | 2016 | 4.716036 |
| 2271 | Portugal | PRT | 2015 | 4.812853 |
| 2272 | Portugal | PRT | 2014 | 4.416001 |
| 2273 | Portugal | PRT | 2013 | 4.451935 |
| 2274 | Portugal | PRT | 2012 | 4.585926 |
| 2275 | Portugal | PRT | 2011 | 4.723430 |
| 2276 | Portugal | PRT | 2010 | 4.817632 |
| 2277 | Puerto Rico | PRI | 2020 | NaN |
| 2278 | Puerto Rico | PRI | 2019 | NaN |
| 2279 | Puerto Rico | PRI | 2018 | NaN |
| 2280 | Puerto Rico | PRI | 2017 | NaN |
| 2281 | Puerto Rico | PRI | 2016 | NaN |
| 2282 | Puerto Rico | PRI | 2015 | NaN |
| 2283 | Puerto Rico | PRI | 2014 | NaN |
| 2284 | Puerto Rico | PRI | 2013 | NaN |
| 2285 | Puerto Rico | PRI | 2012 | NaN |
| 2286 | Puerto Rico | PRI | 2011 | NaN |
| 2287 | Puerto Rico | PRI | 2010 | NaN |
| 2288 | Qatar | QAT | 2020 | 31.726842 |
| 2289 | Qatar | QAT | 2019 | 31.877203 |
| 2290 | Qatar | QAT | 2018 | 31.480967 |
| 2291 | Qatar | QAT | 2017 | 32.256638 |
| 2292 | Qatar | QAT | 2016 | 33.549569 |
| 2293 | Qatar | QAT | 2015 | 35.290422 |
| 2294 | Qatar | QAT | 2014 | 37.105034 |
| 2295 | Qatar | QAT | 2013 | 37.602880 |
| 2296 | Qatar | QAT | 2012 | 39.582140 |
| 2297 | Qatar | QAT | 2011 | 37.979493 |
| 2298 | Qatar | QAT | 2010 | 35.548268 |
| 2299 | Romania | ROU | 2020 | 3.564138 |
| 2300 | Romania | ROU | 2019 | 3.817063 |
| 2301 | Romania | ROU | 2018 | 3.861062 |
| 2302 | Romania | ROU | 2017 | 3.788309 |
| 2303 | Romania | ROU | 2016 | 3.633348 |
| 2304 | Romania | ROU | 2015 | 3.699829 |
| 2305 | Romania | ROU | 2014 | 3.593303 |
| 2306 | Romania | ROU | 2013 | 3.607471 |
| 2307 | Romania | ROU | 2012 | 4.080350 |
| 2308 | Romania | ROU | 2011 | 4.171703 |
| 2309 | Romania | ROU | 2010 | 3.832785 |
| 2310 | Russian Federation | RUS | 2020 | 11.232288 |
| 2311 | Russian Federation | RUS | 2019 | 11.797194 |
| 2312 | Russian Federation | RUS | 2018 | 11.496571 |
| 2313 | Russian Federation | RUS | 2017 | 11.035199 |
| 2314 | Russian Federation | RUS | 2016 | 10.887427 |
| 2315 | Russian Federation | RUS | 2015 | 11.052006 |
| 2316 | Russian Federation | RUS | 2014 | 11.208208 |
| 2317 | Russian Federation | RUS | 2013 | 11.377004 |
| 2318 | Russian Federation | RUS | 2012 | 11.702065 |
| 2319 | Russian Federation | RUS | 2011 | 11.884950 |
| 2320 | Russian Federation | RUS | 2010 | 11.325401 |
| 2321 | Rwanda | RWA | 2020 | 0.105124 |
| 2322 | Rwanda | RWA | 2019 | 0.113058 |
| 2323 | Rwanda | RWA | 2018 | 0.111987 |
| 2324 | Rwanda | RWA | 2017 | 0.102655 |
| 2325 | Rwanda | RWA | 2016 | 0.096221 |
| 2326 | Rwanda | RWA | 2015 | 0.092798 |
| 2327 | Rwanda | RWA | 2014 | 0.081271 |
| 2328 | Rwanda | RWA | 2013 | 0.081404 |
| 2329 | Rwanda | RWA | 2012 | 0.075102 |
| 2330 | Rwanda | RWA | 2011 | 0.069592 |
| 2331 | Rwanda | RWA | 2010 | 0.068259 |
| 2332 | Samoa | WSM | 2020 | 0.960782 |
| 2333 | Samoa | WSM | 2019 | 1.315212 |
| 2334 | Samoa | WSM | 2018 | 1.185974 |
| 2335 | Samoa | WSM | 2017 | 1.229109 |
| 2336 | Samoa | WSM | 2016 | 1.200230 |
| 2337 | Samoa | WSM | 2015 | 1.141125 |
| 2338 | Samoa | WSM | 2014 | 1.027474 |
| 2339 | Samoa | WSM | 2013 | 0.983800 |
| 2340 | Samoa | WSM | 2012 | 0.999879 |
| 2341 | Samoa | WSM | 2011 | 0.998212 |
| 2342 | Samoa | WSM | 2010 | 0.988329 |
| 2343 | San Marino | SMR | 2020 | NaN |
| 2344 | San Marino | SMR | 2019 | NaN |
| 2345 | San Marino | SMR | 2018 | NaN |
| 2346 | San Marino | SMR | 2017 | NaN |
| 2347 | San Marino | SMR | 2016 | NaN |
| 2348 | San Marino | SMR | 2015 | NaN |
| 2349 | San Marino | SMR | 2014 | NaN |
| 2350 | San Marino | SMR | 2013 | NaN |
| 2351 | San Marino | SMR | 2012 | NaN |
| 2352 | San Marino | SMR | 2011 | NaN |
| 2353 | San Marino | SMR | 2010 | NaN |
| 2354 | Sao Tome and Principe | STP | 2020 | 0.645350 |
| 2355 | Sao Tome and Principe | STP | 2019 | 0.653312 |
| 2356 | Sao Tome and Principe | STP | 2018 | 0.650598 |
| 2357 | Sao Tome and Principe | STP | 2017 | 0.646042 |
| 2358 | Sao Tome and Principe | STP | 2016 | 0.628934 |
| 2359 | Sao Tome and Principe | STP | 2015 | 0.614546 |
| 2360 | Sao Tome and Principe | STP | 2014 | 0.603553 |
| 2361 | Sao Tome and Principe | STP | 2013 | 0.626042 |
| 2362 | Sao Tome and Principe | STP | 2012 | 0.624987 |
| 2363 | Sao Tome and Principe | STP | 2011 | 0.540195 |
| 2364 | Sao Tome and Principe | STP | 2010 | 0.564407 |
| 2365 | Saudi Arabia | SAU | 2020 | 14.266585 |
| 2366 | Saudi Arabia | SAU | 2019 | 14.703017 |
| 2367 | Saudi Arabia | SAU | 2018 | 15.065500 |
| 2368 | Saudi Arabia | SAU | 2017 | 16.077792 |
| 2369 | Saudi Arabia | SAU | 2016 | 16.795103 |
| 2370 | Saudi Arabia | SAU | 2015 | 17.257793 |
| 2371 | Saudi Arabia | SAU | 2014 | 16.825236 |
| 2372 | Saudi Arabia | SAU | 2013 | 15.983919 |
| 2373 | Saudi Arabia | SAU | 2012 | 15.978016 |
| 2374 | Saudi Arabia | SAU | 2011 | 15.381398 |
| 2375 | Saudi Arabia | SAU | 2010 | 15.168386 |
| 2376 | Senegal | SEN | 2020 | 0.649801 |
| 2377 | Senegal | SEN | 2019 | 0.768575 |
| 2378 | Senegal | SEN | 2018 | 0.653397 |
| 2379 | Senegal | SEN | 2017 | 0.646585 |
| 2380 | Senegal | SEN | 2016 | 0.686906 |
| 2381 | Senegal | SEN | 2015 | 0.646795 |
| 2382 | Senegal | SEN | 2014 | 0.613587 |
| 2383 | Senegal | SEN | 2013 | 0.589383 |
| 2384 | Senegal | SEN | 2012 | 0.563384 |
| 2385 | Senegal | SEN | 2011 | 0.588030 |
| 2386 | Senegal | SEN | 2010 | 0.560745 |
| 2387 | Serbia | SRB | 2020 | 6.714517 |
| 2388 | Serbia | SRB | 2019 | 6.627580 |
| 2389 | Serbia | SRB | 2018 | 6.615354 |
| 2390 | Serbia | SRB | 2017 | 6.743136 |
| 2391 | Serbia | SRB | 2016 | 6.607094 |
| 2392 | Serbia | SRB | 2015 | 6.399951 |
| 2393 | Serbia | SRB | 2014 | 5.466697 |
| 2394 | Serbia | SRB | 2013 | 6.486829 |
| 2395 | Serbia | SRB | 2012 | 6.360565 |
| 2396 | Serbia | SRB | 2011 | 7.081767 |
| 2397 | Serbia | SRB | 2010 | 6.460168 |
| 2398 | Seychelles | SYC | 2020 | 6.080518 |
| 2399 | Seychelles | SYC | 2019 | 6.097823 |
| 2400 | Seychelles | SYC | 2018 | 6.224551 |
| 2401 | Seychelles | SYC | 2017 | 5.954530 |
| 2402 | Seychelles | SYC | 2016 | 5.973996 |
| 2403 | Seychelles | SYC | 2015 | 5.350089 |
| 2404 | Seychelles | SYC | 2014 | 4.998960 |
| 2405 | Seychelles | SYC | 2013 | 4.582597 |
| 2406 | Seychelles | SYC | 2012 | 4.798251 |
| 2407 | Seychelles | SYC | 2011 | 4.668291 |
| 2408 | Seychelles | SYC | 2010 | 4.942631 |
| 2409 | Sierra Leone | SLE | 2020 | 0.127278 |
| 2410 | Sierra Leone | SLE | 2019 | 0.129094 |
| 2411 | Sierra Leone | SLE | 2018 | 0.132765 |
| 2412 | Sierra Leone | SLE | 2017 | 0.145880 |
| 2413 | Sierra Leone | SLE | 2016 | 0.156233 |
| 2414 | Sierra Leone | SLE | 2015 | 0.148262 |
| 2415 | Sierra Leone | SLE | 2014 | 0.159312 |
| 2416 | Sierra Leone | SLE | 2013 | 0.148000 |
| 2417 | Sierra Leone | SLE | 2012 | 0.125902 |
| 2418 | Sierra Leone | SLE | 2011 | 0.111140 |
| 2419 | Sierra Leone | SLE | 2010 | 0.087032 |
| 2420 | Singapore | SGP | 2020 | 7.686684 |
| 2421 | Singapore | SGP | 2019 | 7.918410 |
| 2422 | Singapore | SGP | 2018 | 8.018212 |
| 2423 | Singapore | SGP | 2017 | 8.432300 |
| 2424 | Singapore | SGP | 2016 | 8.019891 |
| 2425 | Singapore | SGP | 2015 | 8.208109 |
| 2426 | Singapore | SGP | 2014 | 8.117137 |
| 2427 | Singapore | SGP | 2013 | 8.133170 |
| 2428 | Singapore | SGP | 2012 | 8.224530 |
| 2429 | Singapore | SGP | 2011 | 8.636110 |
| 2430 | Singapore | SGP | 2010 | 8.354508 |
| 2431 | Sint Maarten (Dutch part) | SXM | 2020 | NaN |
| 2432 | Sint Maarten (Dutch part) | SXM | 2019 | NaN |
| 2433 | Sint Maarten (Dutch part) | SXM | 2018 | NaN |
| 2434 | Sint Maarten (Dutch part) | SXM | 2017 | NaN |
| 2435 | Sint Maarten (Dutch part) | SXM | 2016 | NaN |
| 2436 | Sint Maarten (Dutch part) | SXM | 2015 | NaN |
| 2437 | Sint Maarten (Dutch part) | SXM | 2014 | NaN |
| 2438 | Sint Maarten (Dutch part) | SXM | 2013 | NaN |
| 2439 | Sint Maarten (Dutch part) | SXM | 2012 | NaN |
| 2440 | Sint Maarten (Dutch part) | SXM | 2011 | NaN |
| 2441 | Sint Maarten (Dutch part) | SXM | 2010 | NaN |
| 2442 | Slovak Republic | SVK | 2020 | 5.319055 |
| 2443 | Slovak Republic | SVK | 2019 | 5.689707 |
| 2444 | Slovak Republic | SVK | 2018 | 6.059572 |
| 2445 | Slovak Republic | SVK | 2017 | 6.173022 |
| 2446 | Slovak Republic | SVK | 2016 | 5.799847 |
| 2447 | Slovak Republic | SVK | 2015 | 5.670138 |
| 2448 | Slovak Republic | SVK | 2014 | 5.617286 |
| 2449 | Slovak Republic | SVK | 2013 | 6.081288 |
| 2450 | Slovak Republic | SVK | 2012 | 5.981808 |
| 2451 | Slovak Republic | SVK | 2011 | 6.319836 |
| 2452 | Slovak Republic | SVK | 2010 | 6.571951 |
| 2453 | Slovenia | SVN | 2020 | 5.934735 |
| 2454 | Slovenia | SVN | 2019 | 6.543334 |
| 2455 | Slovenia | SVN | 2018 | 6.785737 |
| 2456 | Slovenia | SVN | 2017 | 6.834970 |
| 2457 | Slovenia | SVN | 2016 | 6.732551 |
| 2458 | Slovenia | SVN | 2015 | 6.367581 |
| 2459 | Slovenia | SVN | 2014 | 6.359276 |
| 2460 | Slovenia | SVN | 2013 | 7.062346 |
| 2461 | Slovenia | SVN | 2012 | 7.351692 |
| 2462 | Slovenia | SVN | 2011 | 7.648320 |
| 2463 | Slovenia | SVN | 2010 | 7.701519 |
| 2464 | Solomon Islands | SLB | 2020 | 0.323066 |
| 2465 | Solomon Islands | SLB | 2019 | 0.451560 |
| 2466 | Solomon Islands | SLB | 2018 | 0.456428 |
| 2467 | Solomon Islands | SLB | 2017 | 0.458335 |
| 2468 | Solomon Islands | SLB | 2016 | 0.474604 |
| 2469 | Solomon Islands | SLB | 2015 | 0.496360 |
| 2470 | Solomon Islands | SLB | 2014 | 0.570329 |
| 2471 | Solomon Islands | SLB | 2013 | 0.667966 |
| 2472 | Solomon Islands | SLB | 2012 | 0.626318 |
| 2473 | Solomon Islands | SLB | 2011 | 0.642742 |
| 2474 | Solomon Islands | SLB | 2010 | 0.634352 |
| 2475 | Somalia | SOM | 2020 | 0.039935 |
| 2476 | Somalia | SOM | 2019 | 0.041029 |
| 2477 | Somalia | SOM | 2018 | 0.042573 |
| 2478 | Somalia | SOM | 2017 | 0.044059 |
| 2479 | Somalia | SOM | 2016 | 0.045785 |
| 2480 | Somalia | SOM | 2015 | 0.046949 |
| 2481 | Somalia | SOM | 2014 | 0.048530 |
| 2482 | Somalia | SOM | 2013 | 0.050527 |
| 2483 | Somalia | SOM | 2012 | 0.050296 |
| 2484 | Somalia | SOM | 2011 | 0.051773 |
| 2485 | Somalia | SOM | 2010 | 0.052483 |
| 2486 | South Africa | ZAF | 2020 | 6.687563 |
| 2487 | South Africa | ZAF | 2019 | 7.688908 |
| 2488 | South Africa | ZAF | 2018 | 7.667377 |
| 2489 | South Africa | ZAF | 2017 | 7.683708 |
| 2490 | South Africa | ZAF | 2016 | 7.544590 |
| 2491 | South Africa | ZAF | 2015 | 7.607189 |
| 2492 | South Africa | ZAF | 2014 | 8.191153 |
| 2493 | South Africa | ZAF | 2013 | 8.116435 |
| 2494 | South Africa | ZAF | 2012 | 8.034649 |
| 2495 | South Africa | ZAF | 2011 | 7.808054 |
| 2496 | South Africa | ZAF | 2010 | 8.217612 |
| 2497 | South Sudan | SSD | 2020 | 0.164309 |
| 2498 | South Sudan | SSD | 2019 | 0.174642 |
| 2499 | South Sudan | SSD | 2018 | 0.170163 |
| 2500 | South Sudan | SSD | 2017 | 0.141872 |
| 2501 | South Sudan | SSD | 2016 | 0.156351 |
| 2502 | South Sudan | SSD | 2015 | 0.175929 |
| 2503 | South Sudan | SSD | 2014 | 0.135518 |
| 2504 | South Sudan | SSD | 2013 | 0.130839 |
| 2505 | South Sudan | SSD | 2012 | 0.132560 |
| 2506 | South Sudan | SSD | 2011 | 0.125081 |
| 2507 | South Sudan | SSD | 2010 | 0.135186 |
| 2508 | Spain | ESP | 2020 | 4.279595 |
| 2509 | Spain | ESP | 2019 | 5.131799 |
| 2510 | Spain | ESP | 2018 | 5.521060 |
| 2511 | Spain | ESP | 2017 | 5.681591 |
| 2512 | Spain | ESP | 2016 | 5.340585 |
| 2513 | Spain | ESP | 2015 | 5.538855 |
| 2514 | Spain | ESP | 2014 | 5.206009 |
| 2515 | Spain | ESP | 2013 | 5.229401 |
| 2516 | Spain | ESP | 2012 | 5.778549 |
| 2517 | Spain | ESP | 2011 | 5.893329 |
| 2518 | Spain | ESP | 2010 | 5.885763 |
| 2519 | Sri Lanka | LKA | 2020 | 0.996683 |
| 2520 | Sri Lanka | LKA | 2019 | 1.074526 |
| 2521 | Sri Lanka | LKA | 2018 | 1.000937 |
| 2522 | Sri Lanka | LKA | 2017 | 1.075961 |
| 2523 | Sri Lanka | LKA | 2016 | 1.081310 |
| 2524 | Sri Lanka | LKA | 2015 | 0.901775 |
| 2525 | Sri Lanka | LKA | 2014 | 0.821975 |
| 2526 | Sri Lanka | LKA | 2013 | 0.683729 |
| 2527 | Sri Lanka | LKA | 2012 | 0.829818 |
| 2528 | Sri Lanka | LKA | 2011 | 0.738753 |
| 2529 | Sri Lanka | LKA | 2010 | 0.632449 |
| 2530 | St. Kitts and Nevis | KNA | 2020 | 4.848663 |
| 2531 | St. Kitts and Nevis | KNA | 2019 | 5.187374 |
| 2532 | St. Kitts and Nevis | KNA | 2018 | 5.133896 |
| 2533 | St. Kitts and Nevis | KNA | 2017 | 5.085278 |
| 2534 | St. Kitts and Nevis | KNA | 2016 | 5.118440 |
| 2535 | St. Kitts and Nevis | KNA | 2015 | 4.971751 |
| 2536 | St. Kitts and Nevis | KNA | 2014 | 4.779343 |
| 2537 | St. Kitts and Nevis | KNA | 2013 | 4.756422 |
| 2538 | St. Kitts and Nevis | KNA | 2012 | 4.800218 |
| 2539 | St. Kitts and Nevis | KNA | 2011 | 4.968370 |
| 2540 | St. Kitts and Nevis | KNA | 2010 | 4.835137 |
| 2541 | St. Lucia | LCA | 2020 | 2.785139 |
| 2542 | St. Lucia | LCA | 2019 | 2.993566 |
| 2543 | St. Lucia | LCA | 2018 | 2.967598 |
| 2544 | St. Lucia | LCA | 2017 | 2.996675 |
| 2545 | St. Lucia | LCA | 2016 | 2.865435 |
| 2546 | St. Lucia | LCA | 2015 | 2.853840 |
| 2547 | St. Lucia | LCA | 2014 | 2.894099 |
| 2548 | St. Lucia | LCA | 2013 | 2.910713 |
| 2549 | St. Lucia | LCA | 2012 | 2.928537 |
| 2550 | St. Lucia | LCA | 2011 | 2.913823 |
| 2551 | St. Lucia | LCA | 2010 | 2.970135 |
| 2552 | St. Martin (French part) | MAF | 2020 | NaN |
| 2553 | St. Martin (French part) | MAF | 2019 | NaN |
| 2554 | St. Martin (French part) | MAF | 2018 | NaN |
| 2555 | St. Martin (French part) | MAF | 2017 | NaN |
| 2556 | St. Martin (French part) | MAF | 2016 | NaN |
| 2557 | St. Martin (French part) | MAF | 2015 | NaN |
| 2558 | St. Martin (French part) | MAF | 2014 | NaN |
| 2559 | St. Martin (French part) | MAF | 2013 | NaN |
| 2560 | St. Martin (French part) | MAF | 2012 | NaN |
| 2561 | St. Martin (French part) | MAF | 2011 | NaN |
| 2562 | St. Martin (French part) | MAF | 2010 | NaN |
| 2563 | St. Vincent and the Grenadines | VCT | 2020 | 2.100696 |
| 2564 | St. Vincent and the Grenadines | VCT | 2019 | 2.240669 |
| 2565 | St. Vincent and the Grenadines | VCT | 2018 | 2.396444 |
| 2566 | St. Vincent and the Grenadines | VCT | 2017 | 2.132659 |
| 2567 | St. Vincent and the Grenadines | VCT | 2016 | 2.408388 |
| 2568 | St. Vincent and the Grenadines | VCT | 2015 | 2.314945 |
| 2569 | St. Vincent and the Grenadines | VCT | 2014 | 2.502058 |
| 2570 | St. Vincent and the Grenadines | VCT | 2013 | 2.106096 |
| 2571 | St. Vincent and the Grenadines | VCT | 2012 | 2.227917 |
| 2572 | St. Vincent and the Grenadines | VCT | 2011 | 2.068940 |
| 2573 | St. Vincent and the Grenadines | VCT | 2010 | 2.137081 |
| 2574 | Sudan | SDN | 2020 | 0.467954 |
| 2575 | Sudan | SDN | 2019 | 0.511923 |
| 2576 | Sudan | SDN | 2018 | 0.515971 |
| 2577 | Sudan | SDN | 2017 | 0.530472 |
| 2578 | Sudan | SDN | 2016 | 0.546080 |
| 2579 | Sudan | SDN | 2015 | 0.504548 |
| 2580 | Sudan | SDN | 2014 | 0.450190 |
| 2581 | Sudan | SDN | 2013 | 0.440480 |
| 2582 | Sudan | SDN | 2012 | 0.449556 |
| 2583 | Sudan | SDN | 2011 | 0.463009 |
| 2584 | Sudan | SDN | 2010 | 0.486883 |
| 2585 | Suriname | SUR | 2020 | 4.285077 |
| 2586 | Suriname | SUR | 2019 | 4.425813 |
| 2587 | Suriname | SUR | 2018 | 3.615422 |
| 2588 | Suriname | SUR | 2017 | 4.160144 |
| 2589 | Suriname | SUR | 2016 | 5.081900 |
| 2590 | Suriname | SUR | 2015 | 4.733655 |
| 2591 | Suriname | SUR | 2014 | 4.599057 |
| 2592 | Suriname | SUR | 2013 | 4.060328 |
| 2593 | Suriname | SUR | 2012 | 4.374811 |
| 2594 | Suriname | SUR | 2011 | 3.536619 |
| 2595 | Suriname | SUR | 2010 | 3.195264 |
| 2596 | Sweden | SWE | 2020 | 3.242989 |
| 2597 | Sweden | SWE | 2019 | 3.401594 |
| 2598 | Sweden | SWE | 2018 | 3.529744 |
| 2599 | Sweden | SWE | 2017 | 3.794924 |
| 2600 | Sweden | SWE | 2016 | 3.899110 |
| 2601 | Sweden | SWE | 2015 | 3.992179 |
| 2602 | Sweden | SWE | 2014 | 4.021510 |
| 2603 | Sweden | SWE | 2013 | 4.206928 |
| 2604 | Sweden | SWE | 2012 | 4.411698 |
| 2605 | Sweden | SWE | 2011 | 4.704307 |
| 2606 | Sweden | SWE | 2010 | 5.116747 |
| 2607 | Switzerland | CHE | 2020 | 4.042073 |
| 2608 | Switzerland | CHE | 2019 | 4.358610 |
| 2609 | Switzerland | CHE | 2018 | 4.402144 |
| 2610 | Switzerland | CHE | 2017 | 4.578766 |
| 2611 | Switzerland | CHE | 2016 | 4.737239 |
| 2612 | Switzerland | CHE | 2015 | 4.719745 |
| 2613 | Switzerland | CHE | 2014 | 4.859568 |
| 2614 | Switzerland | CHE | 2013 | 5.381300 |
| 2615 | Switzerland | CHE | 2012 | 5.316661 |
| 2616 | Switzerland | CHE | 2011 | 5.206045 |
| 2617 | Switzerland | CHE | 2010 | 5.777422 |
| 2618 | Syrian Arab Republic | SYR | 2020 | 1.214802 |
| 2619 | Syrian Arab Republic | SYR | 2019 | 1.335459 |
| 2620 | Syrian Arab Republic | SYR | 2018 | 1.463944 |
| 2621 | Syrian Arab Republic | SYR | 2017 | 1.358789 |
| 2622 | Syrian Arab Republic | SYR | 2016 | 1.290802 |
| 2623 | Syrian Arab Republic | SYR | 2015 | 1.315307 |
| 2624 | Syrian Arab Republic | SYR | 2014 | 1.325408 |
| 2625 | Syrian Arab Republic | SYR | 2013 | 1.428026 |
| 2626 | Syrian Arab Republic | SYR | 2012 | 1.992393 |
| 2627 | Syrian Arab Republic | SYR | 2011 | 2.532364 |
| 2628 | Syrian Arab Republic | SYR | 2010 | 2.734887 |
| 2629 | Tajikistan | TJK | 2020 | 0.977533 |
| 2630 | Tajikistan | TJK | 2019 | 0.960233 |
| 2631 | Tajikistan | TJK | 2018 | 0.887071 |
| 2632 | Tajikistan | TJK | 2017 | 0.757121 |
| 2633 | Tajikistan | TJK | 2016 | 0.629971 |
| 2634 | Tajikistan | TJK | 2015 | 0.575406 |
| 2635 | Tajikistan | TJK | 2014 | 0.550493 |
| 2636 | Tajikistan | TJK | 2013 | 0.392682 |
| 2637 | Tajikistan | TJK | 2012 | 0.378966 |
| 2638 | Tajikistan | TJK | 2011 | 0.329385 |
| 2639 | Tajikistan | TJK | 2010 | 0.321041 |
| 2640 | Tanzania | TZA | 2020 | 0.233946 |
| 2641 | Tanzania | TZA | 2019 | 0.249877 |
| 2642 | Tanzania | TZA | 2018 | 0.206900 |
| 2643 | Tanzania | TZA | 2017 | 0.207214 |
| 2644 | Tanzania | TZA | 2016 | 0.195709 |
| 2645 | Tanzania | TZA | 2015 | 0.204898 |
| 2646 | Tanzania | TZA | 2014 | 0.198919 |
| 2647 | Tanzania | TZA | 2013 | 0.217202 |
| 2648 | Tanzania | TZA | 2012 | 0.200642 |
| 2649 | Tanzania | TZA | 2011 | 0.172779 |
| 2650 | Tanzania | TZA | 2010 | 0.153177 |
| 2651 | Thailand | THA | 2020 | 3.714256 |
| 2652 | Thailand | THA | 2019 | 3.849044 |
| 2653 | Thailand | THA | 2018 | 3.718428 |
| 2654 | Thailand | THA | 2017 | 3.767897 |
| 2655 | Thailand | THA | 2016 | 3.794470 |
| 2656 | Thailand | THA | 2015 | 3.824676 |
| 2657 | Thailand | THA | 2014 | 3.736042 |
| 2658 | Thailand | THA | 2013 | 3.804057 |
| 2659 | Thailand | THA | 2012 | 3.705856 |
| 2660 | Thailand | THA | 2011 | 3.477785 |
| 2661 | Thailand | THA | 2010 | 3.526682 |
| 2662 | Timor-Leste | TLS | 2020 | 0.343155 |
| 2663 | Timor-Leste | TLS | 2019 | 0.482335 |
| 2664 | Timor-Leste | TLS | 2018 | 0.404249 |
| 2665 | Timor-Leste | TLS | 2017 | 0.451886 |
| 2666 | Timor-Leste | TLS | 2016 | 0.423743 |
| 2667 | Timor-Leste | TLS | 2015 | 0.362577 |
| 2668 | Timor-Leste | TLS | 2014 | 0.379633 |
| 2669 | Timor-Leste | TLS | 2013 | 0.313717 |
| 2670 | Timor-Leste | TLS | 2012 | 0.264047 |
| 2671 | Timor-Leste | TLS | 2011 | 0.226779 |
| 2672 | Timor-Leste | TLS | 2010 | 0.224256 |
| 2673 | Togo | TGO | 2020 | 0.286062 |
| 2674 | Togo | TGO | 2019 | 0.296284 |
| 2675 | Togo | TGO | 2018 | 0.272150 |
| 2676 | Togo | TGO | 2017 | 0.257068 |
| 2677 | Togo | TGO | 2016 | 0.300939 |
| 2678 | Togo | TGO | 2015 | 0.244285 |
| 2679 | Togo | TGO | 2014 | 0.217950 |
| 2680 | Togo | TGO | 2013 | 0.246122 |
| 2681 | Togo | TGO | 2012 | 0.322783 |
| 2682 | Togo | TGO | 2011 | 0.372755 |
| 2683 | Togo | TGO | 2010 | 0.400207 |
| 2684 | Tonga | TON | 2020 | 1.122048 |
| 2685 | Tonga | TON | 2019 | 1.538813 |
| 2686 | Tonga | TON | 2018 | 1.276272 |
| 2687 | Tonga | TON | 2017 | 1.260731 |
| 2688 | Tonga | TON | 2016 | 1.172108 |
| 2689 | Tonga | TON | 2015 | 1.035601 |
| 2690 | Tonga | TON | 2014 | 1.063530 |
| 2691 | Tonga | TON | 2013 | 1.071072 |
| 2692 | Tonga | TON | 2012 | 1.016725 |
| 2693 | Tonga | TON | 2011 | 0.998039 |
| 2694 | Tonga | TON | 2010 | 1.096077 |
| 2695 | Trinidad and Tobago | TTO | 2020 | 10.157119 |
| 2696 | Trinidad and Tobago | TTO | 2019 | 11.313032 |
| 2697 | Trinidad and Tobago | TTO | 2018 | 11.805406 |
| 2698 | Trinidad and Tobago | TTO | 2017 | 12.325588 |
| 2699 | Trinidad and Tobago | TTO | 2016 | 12.448939 |
| 2700 | Trinidad and Tobago | TTO | 2015 | 14.594532 |
| 2701 | Trinidad and Tobago | TTO | 2014 | 15.175289 |
| 2702 | Trinidad and Tobago | TTO | 2013 | 15.399357 |
| 2703 | Trinidad and Tobago | TTO | 2012 | 15.029045 |
| 2704 | Trinidad and Tobago | TTO | 2011 | 15.663864 |
| 2705 | Trinidad and Tobago | TTO | 2010 | 15.204610 |
| 2706 | Tunisia | TUN | 2020 | 2.408623 |
| 2707 | Tunisia | TUN | 2019 | 2.576495 |
| 2708 | Tunisia | TUN | 2018 | 2.599765 |
| 2709 | Tunisia | TUN | 2017 | 2.602781 |
| 2710 | Tunisia | TUN | 2016 | 2.594443 |
| 2711 | Tunisia | TUN | 2015 | 2.736460 |
| 2712 | Tunisia | TUN | 2014 | 2.710311 |
| 2713 | Tunisia | TUN | 2013 | 2.531078 |
| 2714 | Tunisia | TUN | 2012 | 2.604725 |
| 2715 | Tunisia | TUN | 2011 | 2.421693 |
| 2716 | Tunisia | TUN | 2010 | 2.599480 |
| 2717 | Turkiye | TUR | 2020 | 4.885864 |
| 2718 | Turkiye | TUR | 2019 | 4.828961 |
| 2719 | Turkiye | TUR | 2018 | 5.086920 |
| 2720 | Turkiye | TUR | 2017 | 5.205879 |
| 2721 | Turkiye | TUR | 2016 | 4.747839 |
| 2722 | Turkiye | TUR | 2015 | 4.518290 |
| 2723 | Turkiye | TUR | 2014 | 4.426835 |
| 2724 | Turkiye | TUR | 2013 | 4.190395 |
| 2725 | Turkiye | TUR | 2012 | 4.387019 |
| 2726 | Turkiye | TUR | 2011 | 4.292989 |
| 2727 | Turkiye | TUR | 2010 | 4.071715 |
| 2728 | Turkmenistan | TKM | 2020 | 10.184086 |
| 2729 | Turkmenistan | TKM | 2019 | 10.267536 |
| 2730 | Turkmenistan | TKM | 2018 | 10.439722 |
| 2731 | Turkmenistan | TKM | 2017 | 10.701659 |
| 2732 | Turkmenistan | TKM | 2016 | 10.919116 |
| 2733 | Turkmenistan | TKM | 2015 | 11.060151 |
| 2734 | Turkmenistan | TKM | 2014 | 10.981340 |
| 2735 | Turkmenistan | TKM | 2013 | 11.473095 |
| 2736 | Turkmenistan | TKM | 2012 | 12.229784 |
| 2737 | Turkmenistan | TKM | 2011 | 12.139339 |
| 2738 | Turkmenistan | TKM | 2010 | 11.232999 |
| 2739 | Turks and Caicos Islands | TCA | 2020 | NaN |
| 2740 | Turks and Caicos Islands | TCA | 2019 | NaN |
| 2741 | Turks and Caicos Islands | TCA | 2018 | NaN |
| 2742 | Turks and Caicos Islands | TCA | 2017 | NaN |
| 2743 | Turks and Caicos Islands | TCA | 2016 | NaN |
| 2744 | Turks and Caicos Islands | TCA | 2015 | NaN |
| 2745 | Turks and Caicos Islands | TCA | 2014 | NaN |
| 2746 | Turks and Caicos Islands | TCA | 2013 | NaN |
| 2747 | Turks and Caicos Islands | TCA | 2012 | NaN |
| 2748 | Turks and Caicos Islands | TCA | 2011 | NaN |
| 2749 | Turks and Caicos Islands | TCA | 2010 | NaN |
| 2750 | Tuvalu | TUV | 2020 | 0.596260 |
| 2751 | Tuvalu | TUV | 2019 | 0.812340 |
| 2752 | Tuvalu | TUV | 2018 | 0.809940 |
| 2753 | Tuvalu | TUV | 2017 | 0.711119 |
| 2754 | Tuvalu | TUV | 2016 | 0.691117 |
| 2755 | Tuvalu | TUV | 2015 | 0.707916 |
| 2756 | Tuvalu | TUV | 2014 | 0.779888 |
| 2757 | Tuvalu | TUV | 2013 | 0.796849 |
| 2758 | Tuvalu | TUV | 2012 | 0.902893 |
| 2759 | Tuvalu | TUV | 2011 | 0.953271 |
| 2760 | Tuvalu | TUV | 2010 | 0.909953 |
| 2761 | Uganda | UGA | 2020 | 0.127793 |
| 2762 | Uganda | UGA | 2019 | 0.138373 |
| 2763 | Uganda | UGA | 2018 | 0.141311 |
| 2764 | Uganda | UGA | 2017 | 0.128890 |
| 2765 | Uganda | UGA | 2016 | 0.127652 |
| 2766 | Uganda | UGA | 2015 | 0.125732 |
| 2767 | Uganda | UGA | 2014 | 0.113170 |
| 2768 | Uganda | UGA | 2013 | 0.104733 |
| 2769 | Uganda | UGA | 2012 | 0.110205 |
| 2770 | Uganda | UGA | 2011 | 0.112453 |
| 2771 | Uganda | UGA | 2010 | 0.103025 |
| 2772 | Ukraine | UKR | 2020 | 3.753816 |
| 2773 | Ukraine | UKR | 2019 | 3.933653 |
| 2774 | Ukraine | UKR | 2018 | 4.159868 |
| 2775 | Ukraine | UKR | 2017 | 3.902161 |
| 2776 | Ukraine | UKR | 2016 | 4.480766 |
| 2777 | Ukraine | UKR | 2015 | 4.231467 |
| 2778 | Ukraine | UKR | 2014 | 5.251102 |
| 2779 | Ukraine | UKR | 2013 | 5.941323 |
| 2780 | Ukraine | UKR | 2012 | 6.077865 |
| 2781 | Ukraine | UKR | 2011 | 6.199227 |
| 2782 | Ukraine | UKR | 2010 | 5.862661 |
| 2783 | United Arab Emirates | ARE | 2020 | 20.252272 |
| 2784 | United Arab Emirates | ARE | 2019 | 20.153345 |
| 2785 | United Arab Emirates | ARE | 2018 | 19.060950 |
| 2786 | United Arab Emirates | ARE | 2017 | 21.165498 |
| 2787 | United Arab Emirates | ARE | 2016 | 22.280703 |
| 2788 | United Arab Emirates | ARE | 2015 | 21.914502 |
| 2789 | United Arab Emirates | ARE | 2014 | 21.122774 |
| 2790 | United Arab Emirates | ARE | 2013 | 21.133916 |
| 2791 | United Arab Emirates | ARE | 2012 | 20.275652 |
| 2792 | United Arab Emirates | ARE | 2011 | 19.431780 |
| 2793 | United Arab Emirates | ARE | 2010 | 19.192796 |
| 2794 | United Kingdom | GBR | 2020 | 4.601142 |
| 2795 | United Kingdom | GBR | 2019 | 5.175842 |
| 2796 | United Kingdom | GBR | 2018 | 5.425128 |
| 2797 | United Kingdom | GBR | 2017 | 5.553291 |
| 2798 | United Kingdom | GBR | 2016 | 5.824503 |
| 2799 | United Kingdom | GBR | 2015 | 6.159376 |
| 2800 | United Kingdom | GBR | 2014 | 6.433347 |
| 2801 | United Kingdom | GBR | 2013 | 7.076100 |
| 2802 | United Kingdom | GBR | 2012 | 7.344261 |
| 2803 | United Kingdom | GBR | 2011 | 7.044843 |
| 2804 | United Kingdom | GBR | 2010 | 7.689567 |
| 2805 | United States | USA | 2020 | 13.032828 |
| 2806 | United States | USA | 2019 | 14.673381 |
| 2807 | United States | USA | 2018 | 15.222518 |
| 2808 | United States | USA | 2017 | 14.823245 |
| 2809 | United States | USA | 2016 | 15.149883 |
| 2810 | United States | USA | 2015 | 15.560015 |
| 2811 | United States | USA | 2014 | 16.040917 |
| 2812 | United States | USA | 2013 | 16.111175 |
| 2813 | United States | USA | 2012 | 15.789760 |
| 2814 | United States | USA | 2011 | 16.604190 |
| 2815 | United States | USA | 2010 | 17.431737 |
| 2816 | Uruguay | URY | 2020 | 1.899719 |
| 2817 | Uruguay | URY | 2019 | 1.985382 |
| 2818 | Uruguay | URY | 2018 | 1.910015 |
| 2819 | Uruguay | URY | 2017 | 1.783590 |
| 2820 | Uruguay | URY | 2016 | 1.911408 |
| 2821 | Uruguay | URY | 2015 | 1.956379 |
| 2822 | Uruguay | URY | 2014 | 1.916582 |
| 2823 | Uruguay | URY | 2013 | 2.176045 |
| 2824 | Uruguay | URY | 2012 | 2.526658 |
| 2825 | Uruguay | URY | 2011 | 2.262558 |
| 2826 | Uruguay | URY | 2010 | 1.874278 |
| 2827 | Uzbekistan | UZB | 2020 | 3.376304 |
| 2828 | Uzbekistan | UZB | 2019 | 3.504663 |
| 2829 | Uzbekistan | UZB | 2018 | 3.420323 |
| 2830 | Uzbekistan | UZB | 2017 | 3.387257 |
| 2831 | Uzbekistan | UZB | 2016 | 3.307405 |
| 2832 | Uzbekistan | UZB | 2015 | 3.174495 |
| 2833 | Uzbekistan | UZB | 2014 | 3.409634 |
| 2834 | Uzbekistan | UZB | 2013 | 3.698567 |
| 2835 | Uzbekistan | UZB | 2012 | 3.799903 |
| 2836 | Uzbekistan | UZB | 2011 | 4.384333 |
| 2837 | Uzbekistan | UZB | 2010 | 4.419814 |
| 2838 | Vanuatu | VUT | 2020 | 0.389175 |
| 2839 | Vanuatu | VUT | 2019 | 0.548285 |
| 2840 | Vanuatu | VUT | 2018 | 0.597044 |
| 2841 | Vanuatu | VUT | 2017 | 0.485807 |
| 2842 | Vanuatu | VUT | 2016 | 0.534217 |
| 2843 | Vanuatu | VUT | 2015 | 0.485823 |
| 2844 | Vanuatu | VUT | 2014 | 0.588678 |
| 2845 | Vanuatu | VUT | 2013 | 0.424613 |
| 2846 | Vanuatu | VUT | 2012 | 0.468301 |
| 2847 | Vanuatu | VUT | 2011 | 0.534036 |
| 2848 | Vanuatu | VUT | 2010 | 0.517818 |
| 2849 | Venezuela, RB | VEN | 2020 | 2.545028 |
| 2850 | Venezuela, RB | VEN | 2019 | 3.710599 |
| 2851 | Venezuela, RB | VEN | 2018 | 4.363961 |
| 2852 | Venezuela, RB | VEN | 2017 | 4.573681 |
| 2853 | Venezuela, RB | VEN | 2016 | 4.894585 |
| 2854 | Venezuela, RB | VEN | 2015 | 5.343217 |
| 2855 | Venezuela, RB | VEN | 2014 | 5.936295 |
| 2856 | Venezuela, RB | VEN | 2013 | 6.046735 |
| 2857 | Venezuela, RB | VEN | 2012 | 6.146121 |
| 2858 | Venezuela, RB | VEN | 2011 | 5.500369 |
| 2859 | Venezuela, RB | VEN | 2010 | 5.714835 |
| 2860 | Viet Nam | VNM | 2020 | 3.676440 |
| 2861 | Viet Nam | VNM | 2019 | 3.567848 |
| 2862 | Viet Nam | VNM | 2018 | 3.014711 |
| 2863 | Viet Nam | VNM | 2017 | 2.444645 |
| 2864 | Viet Nam | VNM | 2016 | 2.384160 |
| 2865 | Viet Nam | VNM | 2015 | 2.185815 |
| 2866 | Viet Nam | VNM | 2014 | 1.980575 |
| 2867 | Viet Nam | VNM | 2013 | 1.820112 |
| 2868 | Viet Nam | VNM | 2012 | 1.741551 |
| 2869 | Viet Nam | VNM | 2011 | 1.765420 |
| 2870 | Viet Nam | VNM | 2010 | 1.732202 |
| 2871 | Virgin Islands (U.S.) | VIR | 2020 | NaN |
| 2872 | Virgin Islands (U.S.) | VIR | 2019 | NaN |
| 2873 | Virgin Islands (U.S.) | VIR | 2018 | NaN |
| 2874 | Virgin Islands (U.S.) | VIR | 2017 | NaN |
| 2875 | Virgin Islands (U.S.) | VIR | 2016 | NaN |
| 2876 | Virgin Islands (U.S.) | VIR | 2015 | NaN |
| 2877 | Virgin Islands (U.S.) | VIR | 2014 | NaN |
| 2878 | Virgin Islands (U.S.) | VIR | 2013 | NaN |
| 2879 | Virgin Islands (U.S.) | VIR | 2012 | NaN |
| 2880 | Virgin Islands (U.S.) | VIR | 2011 | NaN |
| 2881 | Virgin Islands (U.S.) | VIR | 2010 | NaN |
| 2882 | West Bank and Gaza | PSE | 2020 | NaN |
| 2883 | West Bank and Gaza | PSE | 2019 | NaN |
| 2884 | West Bank and Gaza | PSE | 2018 | NaN |
| 2885 | West Bank and Gaza | PSE | 2017 | NaN |
| 2886 | West Bank and Gaza | PSE | 2016 | NaN |
| 2887 | West Bank and Gaza | PSE | 2015 | NaN |
| 2888 | West Bank and Gaza | PSE | 2014 | NaN |
| 2889 | West Bank and Gaza | PSE | 2013 | NaN |
| 2890 | West Bank and Gaza | PSE | 2012 | NaN |
| 2891 | West Bank and Gaza | PSE | 2011 | NaN |
| 2892 | West Bank and Gaza | PSE | 2010 | NaN |
| 2893 | Yemen, Rep. | YEM | 2020 | 0.308515 |
| 2894 | Yemen, Rep. | YEM | 2019 | 0.354864 |
| 2895 | Yemen, Rep. | YEM | 2018 | 0.368614 |
| 2896 | Yemen, Rep. | YEM | 2017 | 0.322370 |
| 2897 | Yemen, Rep. | YEM | 2016 | 0.342802 |
| 2898 | Yemen, Rep. | YEM | 2015 | 0.475240 |
| 2899 | Yemen, Rep. | YEM | 2014 | 0.988347 |
| 2900 | Yemen, Rep. | YEM | 2013 | 1.031167 |
| 2901 | Yemen, Rep. | YEM | 2012 | 0.801288 |
| 2902 | Yemen, Rep. | YEM | 2011 | 0.900866 |
| 2903 | Yemen, Rep. | YEM | 2010 | 1.027803 |
| 2904 | Zambia | ZMB | 2020 | 0.401903 |
| 2905 | Zambia | ZMB | 2019 | 0.414336 |
| 2906 | Zambia | ZMB | 2018 | 0.440527 |
| 2907 | Zambia | ZMB | 2017 | 0.393726 |
| 2908 | Zambia | ZMB | 2016 | 0.316995 |
| 2909 | Zambia | ZMB | 2015 | 0.305055 |
| 2910 | Zambia | ZMB | 2014 | 0.297755 |
| 2911 | Zambia | ZMB | 2013 | 0.278215 |
| 2912 | Zambia | ZMB | 2012 | 0.273340 |
| 2913 | Zambia | ZMB | 2011 | 0.213847 |
| 2914 | Zambia | ZMB | 2010 | 0.192639 |
| 2915 | Zimbabwe | ZWE | 2020 | 0.530484 |
| 2916 | Zimbabwe | ZWE | 2019 | 0.663338 |
| 2917 | Zimbabwe | ZWE | 2018 | 0.735435 |
| 2918 | Zimbabwe | ZWE | 2017 | 0.663069 |
| 2919 | Zimbabwe | ZWE | 2016 | 0.723062 |
| 2920 | Zimbabwe | ZWE | 2015 | 0.846962 |
| 2921 | Zimbabwe | ZWE | 2014 | 0.866838 |
| 2922 | Zimbabwe | ZWE | 2013 | 0.901248 |
| 2923 | Zimbabwe | ZWE | 2012 | 0.901214 |
| 2924 | Zimbabwe | ZWE | 2011 | 0.871932 |
| 2925 | Zimbabwe | ZWE | 2010 | 0.741290 |
worldbank_CO2 = pd.DataFrame(worldbank_CO2)
excel_worldbank_CO2 = "worldbank_CO2.xlsx"
worldbank_CO2.to_excel(excel_worldbank_CO2, index=False)
indicator = 'NY.GDP.PCAP.CD?date=2010:2020'
url = "http://api.worldbank.org/v2/countries/all/indicators/%s&format=json&per_page=5000" % indicator
response = requests.get(url)
result = response.content
result = json.loads(result)
worldbank_gdp = pd.DataFrame.from_dict(result[1])
worldbank_gdp['country'] = worldbank_gdp[['country']].applymap(lambda x : x['value'])
worldbank_gdp.country.unique()
worldbank_gdp = worldbank_gdp[['country', 'countryiso3code', 'date', 'value']]
worldbank_gdp.columns = ['Country_name', 'countrycode', 'year', 'GDP_per_capita']
worldbank_gdp
| Country_name | countrycode | year | GDP_per_capita | |
|---|---|---|---|---|
| 0 | Africa Eastern and Southern | AFE | 2020 | 1355.805923 |
| 1 | Africa Eastern and Southern | AFE | 2019 | 1507.982881 |
| 2 | Africa Eastern and Southern | AFE | 2018 | 1558.307482 |
| 3 | Africa Eastern and Southern | AFE | 2017 | 1485.522597 |
| 4 | Africa Eastern and Southern | AFE | 2016 | 1346.152564 |
| 5 | Africa Eastern and Southern | AFE | 2015 | 1498.738230 |
| 6 | Africa Eastern and Southern | AFE | 2014 | 1678.554977 |
| 7 | Africa Eastern and Southern | AFE | 2013 | 1696.342890 |
| 8 | Africa Eastern and Southern | AFE | 2012 | 1727.355804 |
| 9 | Africa Eastern and Southern | AFE | 2011 | 1763.278672 |
| 10 | Africa Eastern and Southern | AFE | 2010 | 1627.409881 |
| 11 | Africa Western and Central | AFW | 2020 | 1688.075575 |
| 12 | Africa Western and Central | AFW | 2019 | 1812.446822 |
| 13 | Africa Western and Central | AFW | 2018 | 1735.374911 |
| 14 | Africa Western and Central | AFW | 2017 | 1590.277754 |
| 15 | Africa Western and Central | AFW | 2016 | 1648.762676 |
| 16 | Africa Western and Central | AFW | 2015 | 1882.264038 |
| 17 | Africa Western and Central | AFW | 2014 | 2248.316255 |
| 18 | Africa Western and Central | AFW | 2013 | 2154.150832 |
| 19 | Africa Western and Central | AFW | 2012 | 1957.917784 |
| 20 | Africa Western and Central | AFW | 2011 | 1861.381068 |
| 21 | Africa Western and Central | AFW | 2010 | 1679.887830 |
| 22 | Arab World | ARB | 2020 | 5644.142570 |
| 23 | Arab World | ARB | 2019 | 6504.789633 |
| 24 | Arab World | ARB | 2018 | 6579.417105 |
| 25 | Arab World | ARB | 2017 | 6022.024050 |
| 26 | Arab World | ARB | 2016 | 5972.565951 |
| 27 | Arab World | ARB | 2015 | 6205.500065 |
| 28 | Arab World | ARB | 2014 | 7237.439835 |
| 29 | Arab World | ARB | 2013 | 7292.971715 |
| 30 | Arab World | ARB | 2012 | 7301.478406 |
| 31 | Arab World | ARB | 2011 | 6831.999297 |
| 32 | Arab World | ARB | 2010 | 6396.078487 |
| 33 | Caribbean small states | CSS | 2020 | 8846.494092 |
| 34 | Caribbean small states | CSS | 2019 | 10405.803209 |
| 35 | Caribbean small states | CSS | 2018 | 10378.905763 |
| 36 | Caribbean small states | CSS | 2017 | 10101.698337 |
| 37 | Caribbean small states | CSS | 2016 | 9805.586748 |
| 38 | Caribbean small states | CSS | 2015 | 10484.869963 |
| 39 | Caribbean small states | CSS | 2014 | 10730.903392 |
| 40 | Caribbean small states | CSS | 2013 | 10560.261394 |
| 41 | Caribbean small states | CSS | 2012 | 10464.826975 |
| 42 | Caribbean small states | CSS | 2011 | 9967.736396 |
| 43 | Caribbean small states | CSS | 2010 | 9271.400098 |
| 44 | Central Europe and the Baltics | CEB | 2020 | 16297.964101 |
| 45 | Central Europe and the Baltics | CEB | 2019 | 16349.945827 |
| 46 | Central Europe and the Baltics | CEB | 2018 | 16078.207265 |
| 47 | Central Europe and the Baltics | CEB | 2017 | 14223.338676 |
| 48 | Central Europe and the Baltics | CEB | 2016 | 12783.180837 |
| 49 | Central Europe and the Baltics | CEB | 2015 | 12526.593008 |
| 50 | Central Europe and the Baltics | CEB | 2014 | 14142.318734 |
| 51 | Central Europe and the Baltics | CEB | 2013 | 13667.035465 |
| 52 | Central Europe and the Baltics | CEB | 2012 | 13075.402625 |
| 53 | Central Europe and the Baltics | CEB | 2011 | 13964.093831 |
| 54 | Central Europe and the Baltics | CEB | 2010 | 12607.860470 |
| 55 | Early-demographic dividend | EAR | 2020 | 3242.515083 |
| 56 | Early-demographic dividend | EAR | 2019 | 3521.644206 |
| 57 | Early-demographic dividend | EAR | 2018 | 3493.678564 |
| 58 | Early-demographic dividend | EAR | 2017 | 3498.575677 |
| 59 | Early-demographic dividend | EAR | 2016 | 3278.241801 |
| 60 | Early-demographic dividend | EAR | 2015 | 3227.845551 |
| 61 | Early-demographic dividend | EAR | 2014 | 3440.554275 |
| 62 | Early-demographic dividend | EAR | 2013 | 3373.558109 |
| 63 | Early-demographic dividend | EAR | 2012 | 3375.021425 |
| 64 | Early-demographic dividend | EAR | 2011 | 3274.592048 |
| 65 | Early-demographic dividend | EAR | 2010 | 3015.332652 |
| 66 | East Asia & Pacific | EAS | 2020 | 11487.311342 |
| 67 | East Asia & Pacific | EAS | 2019 | 11484.417272 |
| 68 | East Asia & Pacific | EAS | 2018 | 11312.904364 |
| 69 | East Asia & Pacific | EAS | 2017 | 10454.524326 |
| 70 | East Asia & Pacific | EAS | 2016 | 9856.581539 |
| 71 | East Asia & Pacific | EAS | 2015 | 9586.061906 |
| 72 | East Asia & Pacific | EAS | 2014 | 9695.923458 |
| 73 | East Asia & Pacific | EAS | 2013 | 9468.669123 |
| 74 | East Asia & Pacific | EAS | 2012 | 9436.836164 |
| 75 | East Asia & Pacific | EAS | 2011 | 8893.522785 |
| 76 | East Asia & Pacific | EAS | 2010 | 7726.909712 |
| 77 | East Asia & Pacific (excluding high income) | EAP | 2020 | 8262.990946 |
| 78 | East Asia & Pacific (excluding high income) | EAP | 2019 | 8172.023756 |
| 79 | East Asia & Pacific (excluding high income) | EAP | 2018 | 7944.814368 |
| 80 | East Asia & Pacific (excluding high income) | EAP | 2017 | 7151.338608 |
| 81 | East Asia & Pacific (excluding high income) | EAP | 2016 | 6592.555408 |
| 82 | East Asia & Pacific (excluding high income) | EAP | 2015 | 6500.072750 |
| 83 | East Asia & Pacific (excluding high income) | EAP | 2014 | 6292.357183 |
| 84 | East Asia & Pacific (excluding high income) | EAP | 2013 | 5881.992431 |
| 85 | East Asia & Pacific (excluding high income) | EAP | 2012 | 5376.652825 |
| 86 | East Asia & Pacific (excluding high income) | EAP | 2011 | 4863.695780 |
| 87 | East Asia & Pacific (excluding high income) | EAP | 2010 | 4012.172398 |
| 88 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2020 | 8354.747371 |
| 89 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2019 | 8262.811559 |
| 90 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2018 | 8033.191325 |
| 91 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2017 | 7231.043138 |
| 92 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2016 | 6666.248262 |
| 93 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2015 | 6572.915168 |
| 94 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2014 | 6363.068071 |
| 95 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2013 | 5948.319538 |
| 96 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2012 | 5437.548844 |
| 97 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2011 | 4919.038742 |
| 98 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2010 | 4058.012962 |
| 99 | Euro area | EMU | 2020 | 37914.857805 |
| 100 | Euro area | EMU | 2019 | 38902.824779 |
| 101 | Euro area | EMU | 2018 | 39753.124912 |
| 102 | Euro area | EMU | 2017 | 36877.962222 |
| 103 | Euro area | EMU | 2016 | 34888.741685 |
| 104 | Euro area | EMU | 2015 | 34117.724157 |
| 105 | Euro area | EMU | 2014 | 39593.962152 |
| 106 | Euro area | EMU | 2013 | 38805.905575 |
| 107 | Euro area | EMU | 2012 | 37290.426888 |
| 108 | Euro area | EMU | 2011 | 40329.091058 |
| 109 | Euro area | EMU | 2010 | 37303.161626 |
| 110 | Europe & Central Asia | ECS | 2020 | 24021.796031 |
| 111 | Europe & Central Asia | ECS | 2019 | 24892.393549 |
| 112 | Europe & Central Asia | ECS | 2018 | 25276.819444 |
| 113 | Europe & Central Asia | ECS | 2017 | 23688.057657 |
| 114 | Europe & Central Asia | ECS | 2016 | 22411.242080 |
| 115 | Europe & Central Asia | ECS | 2015 | 22588.588574 |
| 116 | Europe & Central Asia | ECS | 2014 | 26348.269490 |
| 117 | Europe & Central Asia | ECS | 2013 | 26100.946145 |
| 118 | Europe & Central Asia | ECS | 2012 | 25096.864419 |
| 119 | Europe & Central Asia | ECS | 2011 | 26146.890100 |
| 120 | Europe & Central Asia | ECS | 2010 | 23635.810086 |
| 121 | Europe & Central Asia (excluding high income) | ECA | 2020 | 7477.878431 |
| 122 | Europe & Central Asia (excluding high income) | ECA | 2019 | 8153.193434 |
| 123 | Europe & Central Asia (excluding high income) | ECA | 2018 | 8025.155608 |
| 124 | Europe & Central Asia (excluding high income) | ECA | 2017 | 7900.555316 |
| 125 | Europe & Central Asia (excluding high income) | ECA | 2016 | 7075.874655 |
| 126 | Europe & Central Asia (excluding high income) | ECA | 2015 | 7486.327414 |
| 127 | Europe & Central Asia (excluding high income) | ECA | 2014 | 9914.029044 |
| 128 | Europe & Central Asia (excluding high income) | ECA | 2013 | 10762.528056 |
| 129 | Europe & Central Asia (excluding high income) | ECA | 2012 | 10211.120232 |
| 130 | Europe & Central Asia (excluding high income) | ECA | 2011 | 9624.482205 |
| 131 | Europe & Central Asia (excluding high income) | ECA | 2010 | 7790.257411 |
| 132 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2020 | 8455.237621 |
| 133 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2019 | 9039.800280 |
| 134 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2018 | 8897.540803 |
| 135 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2017 | 8565.507961 |
| 136 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2016 | 7670.482889 |
| 137 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2015 | 8020.645993 |
| 138 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2014 | 10318.163840 |
| 139 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2013 | 10974.084175 |
| 140 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2012 | 10423.472573 |
| 141 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2011 | 10026.168863 |
| 142 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2010 | 8281.561566 |
| 143 | European Union | EUU | 2020 | 34356.574618 |
| 144 | European Union | EUU | 2019 | 35079.534296 |
| 145 | European Union | EUU | 2018 | 35751.572584 |
| 146 | European Union | EUU | 2017 | 33090.634399 |
| 147 | European Union | EUU | 2016 | 31174.033875 |
| 148 | European Union | EUU | 2015 | 30487.156175 |
| 149 | European Union | EUU | 2014 | 35282.027301 |
| 150 | European Union | EUU | 2013 | 34564.582548 |
| 151 | European Union | EUU | 2012 | 33169.118097 |
| 152 | European Union | EUU | 2011 | 35767.082737 |
| 153 | European Union | EUU | 2010 | 32965.582963 |
| 154 | Fragile and conflict affected situations | FCS | 2020 | 1700.985671 |
| 155 | Fragile and conflict affected situations | FCS | 2019 | 1919.783251 |
| 156 | Fragile and conflict affected situations | FCS | 2018 | 1852.318463 |
| 157 | Fragile and conflict affected situations | FCS | 2017 | 1690.847142 |
| 158 | Fragile and conflict affected situations | FCS | 2016 | 1662.735974 |
| 159 | Fragile and conflict affected situations | FCS | 2015 | 1845.280587 |
| 160 | Fragile and conflict affected situations | FCS | 2014 | 2396.216367 |
| 161 | Fragile and conflict affected situations | FCS | 2013 | 2311.248937 |
| 162 | Fragile and conflict affected situations | FCS | 2012 | 2279.525176 |
| 163 | Fragile and conflict affected situations | FCS | 2011 | 2088.742057 |
| 164 | Fragile and conflict affected situations | FCS | 2010 | 2295.711882 |
| 165 | Heavily indebted poor countries (HIPC) | HPC | 2020 | 968.465881 |
| 166 | Heavily indebted poor countries (HIPC) | HPC | 2019 | 985.130487 |
| 167 | Heavily indebted poor countries (HIPC) | HPC | 2018 | 977.237530 |
| 168 | Heavily indebted poor countries (HIPC) | HPC | 2017 | 940.611779 |
| 169 | Heavily indebted poor countries (HIPC) | HPC | 2016 | 901.237537 |
| 170 | Heavily indebted poor countries (HIPC) | HPC | 2015 | 917.579421 |
| 171 | Heavily indebted poor countries (HIPC) | HPC | 2014 | 982.518810 |
| 172 | Heavily indebted poor countries (HIPC) | HPC | 2013 | 955.103186 |
| 173 | Heavily indebted poor countries (HIPC) | HPC | 2012 | 876.366856 |
| 174 | Heavily indebted poor countries (HIPC) | HPC | 2011 | 872.425638 |
| 175 | Heavily indebted poor countries (HIPC) | HPC | 2010 | 809.616317 |
| 176 | High income | 2020 | 43457.698244 | |
| 177 | High income | 2019 | 44725.995093 | |
| 178 | High income | 2018 | 44528.168742 | |
| 179 | High income | 2017 | 42077.843001 | |
| 180 | High income | 2016 | 40428.179375 | |
| 181 | High income | 2015 | 39811.480182 | |
| 182 | High income | 2014 | 42412.129717 | |
| 183 | High income | 2013 | 41752.361919 | |
| 184 | High income | 2012 | 41480.864148 | |
| 185 | High income | 2011 | 41688.734843 | |
| 186 | High income | 2010 | 38768.187711 | |
| 187 | IBRD only | IBD | 2020 | 6177.526395 |
| 188 | IBRD only | IBD | 2019 | 6460.501165 |
| 189 | IBRD only | IBD | 2018 | 6373.970462 |
| 190 | IBRD only | IBD | 2017 | 6043.460397 |
| 191 | IBRD only | IBD | 2016 | 5523.361421 |
| 192 | IBRD only | IBD | 2015 | 5536.382163 |
| 193 | IBRD only | IBD | 2014 | 5971.514742 |
| 194 | IBRD only | IBD | 2013 | 5839.260740 |
| 195 | IBRD only | IBD | 2012 | 5596.079933 |
| 196 | IBRD only | IBD | 2011 | 5320.923001 |
| 197 | IBRD only | IBD | 2010 | 4541.138234 |
| 198 | IDA & IBRD total | IBT | 2020 | 4901.569304 |
| 199 | IDA & IBRD total | IBT | 2019 | 5140.641855 |
| 200 | IDA & IBRD total | IBT | 2018 | 5084.854052 |
| 201 | IDA & IBRD total | IBT | 2017 | 4833.730926 |
| 202 | IDA & IBRD total | IBT | 2016 | 4453.446424 |
| 203 | IDA & IBRD total | IBT | 2015 | 4480.953737 |
| 204 | IDA & IBRD total | IBT | 2014 | 4832.439720 |
| 205 | IDA & IBRD total | IBT | 2013 | 4723.568041 |
| 206 | IDA & IBRD total | IBT | 2012 | 4528.992032 |
| 207 | IDA & IBRD total | IBT | 2011 | 4321.532936 |
| 208 | IDA & IBRD total | IBT | 2010 | 3745.008547 |
| 209 | IDA blend | IDB | 2020 | 1722.417770 |
| 210 | IDA blend | IDB | 2019 | 1876.654806 |
| 211 | IDA blend | IDB | 2018 | 1877.776724 |
| 212 | IDA blend | IDB | 2017 | 1753.270831 |
| 213 | IDA blend | IDB | 2016 | 1820.081190 |
| 214 | IDA blend | IDB | 2015 | 1987.567534 |
| 215 | IDA blend | IDB | 2014 | 2135.840663 |
| 216 | IDA blend | IDB | 2013 | 2008.212960 |
| 217 | IDA blend | IDB | 2012 | 1885.398591 |
| 218 | IDA blend | IDB | 2011 | 1734.112395 |
| 219 | IDA blend | IDB | 2010 | 1553.523173 |
| 220 | IDA only | IDX | 2020 | 1200.249071 |
| 221 | IDA only | IDX | 2019 | 1214.582592 |
| 222 | IDA only | IDX | 2018 | 1181.353141 |
| 223 | IDA only | IDX | 2017 | 1135.827025 |
| 224 | IDA only | IDX | 2016 | 1077.194178 |
| 225 | IDA only | IDX | 2015 | 1041.905191 |
| 226 | IDA only | IDX | 2014 | 1068.566879 |
| 227 | IDA only | IDX | 2013 | 1021.094144 |
| 228 | IDA only | IDX | 2012 | 958.983338 |
| 229 | IDA only | IDX | 2011 | 979.639015 |
| 230 | IDA only | IDX | 2010 | 1100.591876 |
| 231 | IDA total | IDA | 2020 | 1373.087617 |
| 232 | IDA total | IDA | 2019 | 1434.100097 |
| 233 | IDA total | IDA | 2018 | 1412.711942 |
| 234 | IDA total | IDA | 2017 | 1341.335826 |
| 235 | IDA total | IDA | 2016 | 1325.019041 |
| 236 | IDA total | IDA | 2015 | 1358.115606 |
| 237 | IDA total | IDA | 2014 | 1425.936842 |
| 238 | IDA total | IDA | 2013 | 1351.832980 |
| 239 | IDA total | IDA | 2012 | 1269.489256 |
| 240 | IDA total | IDA | 2011 | 1232.377128 |
| 241 | IDA total | IDA | 2010 | 1251.695026 |
| 242 | Late-demographic dividend | LTE | 2020 | 9722.310421 |
| 243 | Late-demographic dividend | LTE | 2019 | 9979.383421 |
| 244 | Late-demographic dividend | LTE | 2018 | 9840.394631 |
| 245 | Late-demographic dividend | LTE | 2017 | 9022.301890 |
| 246 | Late-demographic dividend | LTE | 2016 | 8182.344735 |
| 247 | Late-demographic dividend | LTE | 2015 | 8213.980431 |
| 248 | Late-demographic dividend | LTE | 2014 | 8812.628633 |
| 249 | Late-demographic dividend | LTE | 2013 | 8544.801775 |
| 250 | Late-demographic dividend | LTE | 2012 | 7991.471281 |
| 251 | Late-demographic dividend | LTE | 2011 | 7525.550318 |
| 252 | Late-demographic dividend | LTE | 2010 | 6214.135223 |
| 253 | Latin America & Caribbean | LCN | 2020 | 7393.174719 |
| 254 | Latin America & Caribbean | LCN | 2019 | 8772.562194 |
| 255 | Latin America & Caribbean | LCN | 2018 | 8977.992553 |
| 256 | Latin America & Caribbean | LCN | 2017 | 9255.805976 |
| 257 | Latin America & Caribbean | LCN | 2016 | 8421.148077 |
| 258 | Latin America & Caribbean | LCN | 2015 | 8723.135457 |
| 259 | Latin America & Caribbean | LCN | 2014 | 10539.374413 |
| 260 | Latin America & Caribbean | LCN | 2013 | 10450.940941 |
| 261 | Latin America & Caribbean | LCN | 2012 | 10311.907063 |
| 262 | Latin America & Caribbean | LCN | 2011 | 10306.430656 |
| 263 | Latin America & Caribbean | LCN | 2010 | 9164.566397 |
| 264 | Latin America & Caribbean (excluding high income) | LAC | 2020 | 6889.469861 |
| 265 | Latin America & Caribbean (excluding high income) | LAC | 2019 | 8246.516673 |
| 266 | Latin America & Caribbean (excluding high income) | LAC | 2018 | 8446.592322 |
| 267 | Latin America & Caribbean (excluding high income) | LAC | 2017 | 8788.350268 |
| 268 | Latin America & Caribbean (excluding high income) | LAC | 2016 | 7972.032188 |
| 269 | Latin America & Caribbean (excluding high income) | LAC | 2015 | 8301.026794 |
| 270 | Latin America & Caribbean (excluding high income) | LAC | 2014 | 9870.617654 |
| 271 | Latin America & Caribbean (excluding high income) | LAC | 2013 | 9937.196527 |
| 272 | Latin America & Caribbean (excluding high income) | LAC | 2012 | 9792.188957 |
| 273 | Latin America & Caribbean (excluding high income) | LAC | 2011 | 9945.024681 |
| 274 | Latin America & Caribbean (excluding high income) | LAC | 2010 | 8616.309422 |
| 275 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2020 | 7186.562493 |
| 276 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2019 | 8593.061308 |
| 277 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2018 | 8817.701109 |
| 278 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2017 | 9106.598873 |
| 279 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2016 | 8258.066184 |
| 280 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2015 | 8577.487766 |
| 281 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2014 | 10460.214588 |
| 282 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2013 | 10377.011616 |
| 283 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2012 | 10241.575135 |
| 284 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2011 | 10246.029957 |
| 285 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2010 | 9093.173824 |
| 286 | Least developed countries: UN classification | LDC | 2020 | 1081.352515 |
| 287 | Least developed countries: UN classification | LDC | 2019 | 1098.256155 |
| 288 | Least developed countries: UN classification | LDC | 2018 | 1066.106183 |
| 289 | Least developed countries: UN classification | LDC | 2017 | 1026.438061 |
| 290 | Least developed countries: UN classification | LDC | 2016 | 960.902427 |
| 291 | Least developed countries: UN classification | LDC | 2015 | 968.005629 |
| 292 | Least developed countries: UN classification | LDC | 2014 | 1033.131858 |
| 293 | Least developed countries: UN classification | LDC | 2013 | 984.483065 |
| 294 | Least developed countries: UN classification | LDC | 2012 | 927.548491 |
| 295 | Least developed countries: UN classification | LDC | 2011 | 910.476918 |
| 296 | Least developed countries: UN classification | LDC | 2010 | 817.691696 |
| 297 | Low & middle income | LMY | 2020 | 4735.357322 |
| 298 | Low & middle income | LMY | 2019 | 4966.260460 |
| 299 | Low & middle income | LMY | 2018 | 4908.171921 |
| 300 | Low & middle income | LMY | 2017 | 4674.839624 |
| 301 | Low & middle income | LMY | 2016 | 4310.379277 |
| 302 | Low & middle income | LMY | 2015 | 4337.193706 |
| 303 | Low & middle income | LMY | 2014 | 4635.922672 |
| 304 | Low & middle income | LMY | 2013 | 4544.044066 |
| 305 | Low & middle income | LMY | 2012 | 4351.161244 |
| 306 | Low & middle income | LMY | 2011 | 4144.792186 |
| 307 | Low & middle income | LMY | 2010 | 3564.243114 |
| 308 | Low income | 2020 | 656.686675 | |
| 309 | Low income | 2019 | 686.222679 | |
| 310 | Low income | 2018 | 662.855807 | |
| 311 | Low income | 2017 | 654.447288 | |
| 312 | Low income | 2016 | 641.935520 | |
| 313 | Low income | 2015 | 714.589027 | |
| 314 | Low income | 2014 | 743.348839 | |
| 315 | Low income | 2013 | 711.636616 | |
| 316 | Low income | 2012 | 709.897752 | |
| 317 | Low income | 2011 | 775.871568 | |
| 318 | Low income | 2010 | 1132.485019 | |
| 319 | Lower middle income | 2020 | 2123.350264 | |
| 320 | Lower middle income | 2019 | 2238.518820 | |
| 321 | Lower middle income | 2018 | 2179.954062 | |
| 322 | Lower middle income | 2017 | 2159.486290 | |
| 323 | Lower middle income | 2016 | 2037.725326 | |
| 324 | Lower middle income | 2015 | 1979.555371 | |
| 325 | Lower middle income | 2014 | 2062.519920 | |
| 326 | Lower middle income | 2013 | 1991.813175 | |
| 327 | Lower middle income | 2012 | 1982.964483 | |
| 328 | Lower middle income | 2011 | 1912.065826 | |
| 329 | Lower middle income | 2010 | 1702.703066 | |
| 330 | Middle East & North Africa | MEA | 2020 | 6579.706726 |
| 331 | Middle East & North Africa | MEA | 2019 | 7444.855634 |
| 332 | Middle East & North Africa | MEA | 2018 | 7565.281634 |
| 333 | Middle East & North Africa | MEA | 2017 | 7337.213549 |
| 334 | Middle East & North Africa | MEA | 2016 | 7158.049769 |
| 335 | Middle East & North Africa | MEA | 2015 | 7217.651624 |
| 336 | Middle East & North Africa | MEA | 2014 | 8345.566904 |
| 337 | Middle East & North Africa | MEA | 2013 | 8471.775586 |
| 338 | Middle East & North Africa | MEA | 2012 | 8794.729803 |
| 339 | Middle East & North Africa | MEA | 2011 | 8320.323020 |
| 340 | Middle East & North Africa | MEA | 2010 | 7524.725208 |
| 341 | Middle East & North Africa (excluding high inc... | MNA | 2020 | 3120.088264 |
| 342 | Middle East & North Africa (excluding high inc... | MNA | 2019 | 3475.858429 |
| 343 | Middle East & North Africa (excluding high inc... | MNA | 2018 | 3518.886053 |
| 344 | Middle East & North Africa (excluding high inc... | MNA | 2017 | 3771.398833 |
| 345 | Middle East & North Africa (excluding high inc... | MNA | 2016 | 3832.820485 |
| 346 | Middle East & North Africa (excluding high inc... | MNA | 2015 | 3805.679938 |
| 347 | Middle East & North Africa (excluding high inc... | MNA | 2014 | 4317.813304 |
| 348 | Middle East & North Africa (excluding high inc... | MNA | 2013 | 4470.139956 |
| 349 | Middle East & North Africa (excluding high inc... | MNA | 2012 | 4953.991470 |
| 350 | Middle East & North Africa (excluding high inc... | MNA | 2011 | 4678.504037 |
| 351 | Middle East & North Africa (excluding high inc... | MNA | 2010 | 4624.872345 |
| 352 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2020 | 3118.749032 |
| 353 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2019 | 3473.741368 |
| 354 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2018 | 3518.381989 |
| 355 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2017 | 3773.136769 |
| 356 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2016 | 3836.321689 |
| 357 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2015 | 3811.773554 |
| 358 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2014 | 4328.807414 |
| 359 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2013 | 4483.245513 |
| 360 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2012 | 4975.306641 |
| 361 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2011 | 4698.685374 |
| 362 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2010 | 4647.930916 |
| 363 | Middle income | MIC | 2020 | 5197.802353 |
| 364 | Middle income | MIC | 2019 | 5442.662294 |
| 365 | Middle income | MIC | 2018 | 5372.268908 |
| 366 | Middle income | MIC | 2017 | 5107.250279 |
| 367 | Middle income | MIC | 2016 | 4698.955699 |
| 368 | Middle income | MIC | 2015 | 4715.505443 |
| 369 | Middle income | MIC | 2014 | 5036.885976 |
| 370 | Middle income | MIC | 2013 | 4933.771524 |
| 371 | Middle income | MIC | 2012 | 4716.812531 |
| 372 | Middle income | MIC | 2011 | 4478.614654 |
| 373 | Middle income | MIC | 2010 | 3803.998412 |
| 374 | North America | NAC | 2020 | 61483.000750 |
| 375 | North America | NAC | 2019 | 63203.373889 |
| 376 | North America | NAC | 2018 | 61174.777344 |
| 377 | North America | NAC | 2017 | 58423.885879 |
| 378 | North America | NAC | 2016 | 56312.434885 |
| 379 | North America | NAC | 2015 | 55452.421384 |
| 380 | North America | NAC | 2014 | 54714.470929 |
| 381 | North America | NAC | 2013 | 53234.150098 |
| 382 | North America | NAC | 2012 | 51881.170886 |
| 383 | North America | NAC | 2011 | 50289.024404 |
| 384 | North America | NAC | 2010 | 48552.942406 |
| 385 | Not classified | 2020 | NaN | |
| 386 | Not classified | 2019 | NaN | |
| 387 | Not classified | 2018 | NaN | |
| 388 | Not classified | 2017 | NaN | |
| 389 | Not classified | 2016 | NaN | |
| 390 | Not classified | 2015 | NaN | |
| 391 | Not classified | 2014 | NaN | |
| 392 | Not classified | 2013 | NaN | |
| 393 | Not classified | 2012 | NaN | |
| 394 | Not classified | 2011 | NaN | |
| 395 | Not classified | 2010 | NaN | |
| 396 | OECD members | OED | 2020 | 38402.117597 |
| 397 | OECD members | OED | 2019 | 39583.225700 |
| 398 | OECD members | OED | 2018 | 39416.242611 |
| 399 | OECD members | OED | 2017 | 37476.546622 |
| 400 | OECD members | OED | 2016 | 36115.193067 |
| 401 | OECD members | OED | 2015 | 35666.456739 |
| 402 | OECD members | OED | 2014 | 38068.495267 |
| 403 | OECD members | OED | 2013 | 37546.478501 |
| 404 | OECD members | OED | 2012 | 37285.584018 |
| 405 | OECD members | OED | 2011 | 37547.352934 |
| 406 | OECD members | OED | 2010 | 35088.330213 |
| 407 | Other small states | OSS | 2020 | 11686.934107 |
| 408 | Other small states | OSS | 2019 | 13574.607787 |
| 409 | Other small states | OSS | 2018 | 14076.263506 |
| 410 | Other small states | OSS | 2017 | 12902.170196 |
| 411 | Other small states | OSS | 2016 | 12088.909771 |
| 412 | Other small states | OSS | 2015 | 12502.872877 |
| 413 | Other small states | OSS | 2014 | 15445.715680 |
| 414 | Other small states | OSS | 2013 | 15303.842945 |
| 415 | Other small states | OSS | 2012 | 14987.307257 |
| 416 | Other small states | OSS | 2011 | 14660.135838 |
| 417 | Other small states | OSS | 2010 | 12139.092784 |
| 418 | Pacific island small states | PSS | 2020 | 3698.099060 |
| 419 | Pacific island small states | PSS | 2019 | 4222.882129 |
| 420 | Pacific island small states | PSS | 2018 | 4288.226218 |
| 421 | Pacific island small states | PSS | 2017 | 4128.661018 |
| 422 | Pacific island small states | PSS | 2016 | 3866.861860 |
| 423 | Pacific island small states | PSS | 2015 | 3723.875114 |
| 424 | Pacific island small states | PSS | 2014 | 3851.251339 |
| 425 | Pacific island small states | PSS | 2013 | 3582.878279 |
| 426 | Pacific island small states | PSS | 2012 | 3484.174056 |
| 427 | Pacific island small states | PSS | 2011 | 3324.395457 |
| 428 | Pacific island small states | PSS | 2010 | 2882.716204 |
| 429 | Post-demographic dividend | PST | 2020 | 44514.122675 |
| 430 | Post-demographic dividend | PST | 2019 | 45700.060804 |
| 431 | Post-demographic dividend | PST | 2018 | 45382.763953 |
| 432 | Post-demographic dividend | PST | 2017 | 42968.289527 |
| 433 | Post-demographic dividend | PST | 2016 | 41363.385868 |
| 434 | Post-demographic dividend | PST | 2015 | 40636.347202 |
| 435 | Post-demographic dividend | PST | 2014 | 43170.295238 |
| 436 | Post-demographic dividend | PST | 2013 | 42523.743382 |
| 437 | Post-demographic dividend | PST | 2012 | 42291.078498 |
| 438 | Post-demographic dividend | PST | 2011 | 42530.783738 |
| 439 | Post-demographic dividend | PST | 2010 | 39705.650032 |
| 440 | Pre-demographic dividend | PRE | 2020 | 1330.420770 |
| 441 | Pre-demographic dividend | PRE | 2019 | 1489.898830 |
| 442 | Pre-demographic dividend | PRE | 2018 | 1452.899967 |
| 443 | Pre-demographic dividend | PRE | 2017 | 1340.519674 |
| 444 | Pre-demographic dividend | PRE | 2016 | 1320.209969 |
| 445 | Pre-demographic dividend | PRE | 2015 | 1524.635701 |
| 446 | Pre-demographic dividend | PRE | 2014 | 1844.458296 |
| 447 | Pre-demographic dividend | PRE | 2013 | 1791.566219 |
| 448 | Pre-demographic dividend | PRE | 2012 | 1682.707272 |
| 449 | Pre-demographic dividend | PRE | 2011 | 1595.912123 |
| 450 | Pre-demographic dividend | PRE | 2010 | 1418.522810 |
| 451 | Small states | SST | 2020 | 10704.407265 |
| 452 | Small states | SST | 2019 | 12448.873754 |
| 453 | Small states | SST | 2018 | 12823.540018 |
| 454 | Small states | SST | 2017 | 11864.822232 |
| 455 | Small states | SST | 2016 | 11169.739312 |
| 456 | Small states | SST | 2015 | 11588.223406 |
| 457 | Small states | SST | 2014 | 13841.681641 |
| 458 | Small states | SST | 2013 | 13668.087354 |
| 459 | Small states | SST | 2012 | 13391.828131 |
| 460 | Small states | SST | 2011 | 13029.263385 |
| 461 | Small states | SST | 2010 | 10985.285204 |
| 462 | South Asia | SAS | 2020 | 1853.845901 |
| 463 | South Asia | SAS | 2019 | 1965.094236 |
| 464 | South Asia | SAS | 2018 | 1920.140055 |
| 465 | South Asia | SAS | 2017 | 1887.890561 |
| 466 | South Asia | SAS | 2016 | 1675.438752 |
| 467 | South Asia | SAS | 2015 | 1539.470601 |
| 468 | South Asia | SAS | 2014 | 1490.717749 |
| 469 | South Asia | SAS | 2013 | 1380.003413 |
| 470 | South Asia | SAS | 2012 | 1362.331774 |
| 471 | South Asia | SAS | 2011 | 1361.483067 |
| 472 | South Asia | SAS | 2010 | 1253.946408 |
| 473 | South Asia (IDA & IBRD) | TSA | 2020 | 1853.845901 |
| 474 | South Asia (IDA & IBRD) | TSA | 2019 | 1965.094236 |
| 475 | South Asia (IDA & IBRD) | TSA | 2018 | 1920.140055 |
| 476 | South Asia (IDA & IBRD) | TSA | 2017 | 1887.890561 |
| 477 | South Asia (IDA & IBRD) | TSA | 2016 | 1675.438752 |
| 478 | South Asia (IDA & IBRD) | TSA | 2015 | 1539.470601 |
| 479 | South Asia (IDA & IBRD) | TSA | 2014 | 1490.717749 |
| 480 | South Asia (IDA & IBRD) | TSA | 2013 | 1380.003413 |
| 481 | South Asia (IDA & IBRD) | TSA | 2012 | 1362.331774 |
| 482 | South Asia (IDA & IBRD) | TSA | 2011 | 1361.483067 |
| 483 | South Asia (IDA & IBRD) | TSA | 2010 | 1253.946408 |
| 484 | Sub-Saharan Africa | SSF | 2020 | 1490.349666 |
| 485 | Sub-Saharan Africa | SSF | 2019 | 1631.312141 |
| 486 | Sub-Saharan Africa | SSF | 2018 | 1630.055972 |
| 487 | Sub-Saharan Africa | SSF | 2017 | 1527.974545 |
| 488 | Sub-Saharan Africa | SSF | 2016 | 1468.749147 |
| 489 | Sub-Saharan Africa | SSF | 2015 | 1654.129816 |
| 490 | Sub-Saharan Africa | SSF | 2014 | 1909.508758 |
| 491 | Sub-Saharan Africa | SSF | 2013 | 1881.942232 |
| 492 | Sub-Saharan Africa | SSF | 2012 | 1820.526912 |
| 493 | Sub-Saharan Africa | SSF | 2011 | 1802.537519 |
| 494 | Sub-Saharan Africa | SSF | 2010 | 1648.150038 |
| 495 | Sub-Saharan Africa (excluding high income) | SSA | 2020 | 1489.449067 |
| 496 | Sub-Saharan Africa (excluding high income) | SSA | 2019 | 1629.987221 |
| 497 | Sub-Saharan Africa (excluding high income) | SSA | 2018 | 1628.746521 |
| 498 | Sub-Saharan Africa (excluding high income) | SSA | 2017 | 1526.674168 |
| 499 | Sub-Saharan Africa (excluding high income) | SSA | 2016 | 1467.475190 |
| 500 | Sub-Saharan Africa (excluding high income) | SSA | 2015 | 1652.903468 |
| 501 | Sub-Saharan Africa (excluding high income) | SSA | 2014 | 1908.272660 |
| 502 | Sub-Saharan Africa (excluding high income) | SSA | 2013 | 1880.732150 |
| 503 | Sub-Saharan Africa (excluding high income) | SSA | 2012 | 1819.527590 |
| 504 | Sub-Saharan Africa (excluding high income) | SSA | 2011 | 1801.540864 |
| 505 | Sub-Saharan Africa (excluding high income) | SSA | 2010 | 1647.202359 |
| 506 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2020 | 1490.349666 |
| 507 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2019 | 1631.312141 |
| 508 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2018 | 1630.055972 |
| 509 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2017 | 1527.974545 |
| 510 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2016 | 1468.749147 |
| 511 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2015 | 1654.129816 |
| 512 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2014 | 1909.508758 |
| 513 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2013 | 1881.942232 |
| 514 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2012 | 1820.526912 |
| 515 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2011 | 1802.537519 |
| 516 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2010 | 1648.150038 |
| 517 | Upper middle income | 2020 | 8663.002093 | |
| 518 | Upper middle income | 2019 | 9023.202992 | |
| 519 | Upper middle income | 2018 | 8912.567581 | |
| 520 | Upper middle income | 2017 | 8352.326026 | |
| 521 | Upper middle income | 2016 | 7607.596731 | |
| 522 | Upper middle income | 2015 | 7683.611108 | |
| 523 | Upper middle income | 2014 | 8239.684335 | |
| 524 | Upper middle income | 2013 | 8078.037981 | |
| 525 | Upper middle income | 2012 | 7617.695422 | |
| 526 | Upper middle income | 2011 | 7182.160175 | |
| 527 | Upper middle income | 2010 | 5998.634642 | |
| 528 | World | WLD | 2020 | 10904.147614 |
| 529 | World | WLD | 2019 | 11338.150319 |
| 530 | World | WLD | 2018 | 11297.452401 |
| 531 | World | WLD | 2017 | 10743.214166 |
| 532 | World | WLD | 2016 | 10207.503576 |
| 533 | World | WLD | 2015 | 10163.615240 |
| 534 | World | WLD | 2014 | 10907.394415 |
| 535 | World | WLD | 2013 | 10746.777539 |
| 536 | World | WLD | 2012 | 10584.356145 |
| 537 | World | WLD | 2011 | 10482.177890 |
| 538 | World | WLD | 2010 | 9568.438602 |
| 539 | Afghanistan | AFG | 2020 | 512.055098 |
| 540 | Afghanistan | AFG | 2019 | 497.741429 |
| 541 | Afghanistan | AFG | 2018 | 492.090632 |
| 542 | Afghanistan | AFG | 2017 | 526.140801 |
| 543 | Afghanistan | AFG | 2016 | 523.053012 |
| 544 | Afghanistan | AFG | 2015 | 566.881133 |
| 545 | Afghanistan | AFG | 2014 | 626.512930 |
| 546 | Afghanistan | AFG | 2013 | 638.733185 |
| 547 | Afghanistan | AFG | 2012 | 653.417479 |
| 548 | Afghanistan | AFG | 2011 | 608.738856 |
| 549 | Afghanistan | AFG | 2010 | 562.499219 |
| 550 | Albania | ALB | 2020 | 5343.037704 |
| 551 | Albania | ALB | 2019 | 5396.214243 |
| 552 | Albania | ALB | 2018 | 5287.660801 |
| 553 | Albania | ALB | 2017 | 4531.032207 |
| 554 | Albania | ALB | 2016 | 4124.055390 |
| 555 | Albania | ALB | 2015 | 3952.803574 |
| 556 | Albania | ALB | 2014 | 4578.633208 |
| 557 | Albania | ALB | 2013 | 4413.063383 |
| 558 | Albania | ALB | 2012 | 4247.631343 |
| 559 | Albania | ALB | 2011 | 4437.141161 |
| 560 | Albania | ALB | 2010 | 4094.349686 |
| 561 | Algeria | DZA | 2020 | 3354.153164 |
| 562 | Algeria | DZA | 2019 | 4021.983266 |
| 563 | Algeria | DZA | 2018 | 4171.790388 |
| 564 | Algeria | DZA | 2017 | 4134.936087 |
| 565 | Algeria | DZA | 2016 | 3967.200647 |
| 566 | Algeria | DZA | 2015 | 4197.419985 |
| 567 | Algeria | DZA | 2014 | 5516.229440 |
| 568 | Algeria | DZA | 2013 | 5519.777576 |
| 569 | Algeria | DZA | 2012 | 5610.733282 |
| 570 | Algeria | DZA | 2011 | 5473.281826 |
| 571 | Algeria | DZA | 2010 | 4495.921476 |
| 572 | American Samoa | ASM | 2020 | 15609.777220 |
| 573 | American Samoa | ASM | 2019 | 13672.576657 |
| 574 | American Samoa | ASM | 2018 | 13195.935900 |
| 575 | American Samoa | ASM | 2017 | 12372.884783 |
| 576 | American Samoa | ASM | 2016 | 13300.824611 |
| 577 | American Samoa | ASM | 2015 | 13101.541816 |
| 578 | American Samoa | ASM | 2014 | 12313.997357 |
| 579 | American Samoa | ASM | 2013 | 12038.871592 |
| 580 | American Samoa | ASM | 2012 | 11920.061090 |
| 581 | American Samoa | ASM | 2011 | 10495.304732 |
| 582 | American Samoa | ASM | 2010 | 10446.863206 |
| 583 | Andorra | AND | 2020 | 37207.238871 |
| 584 | Andorra | AND | 2019 | 41328.612393 |
| 585 | Andorra | AND | 2018 | 42904.811588 |
| 586 | Andorra | AND | 2017 | 40632.208982 |
| 587 | Andorra | AND | 2016 | 39931.236264 |
| 588 | Andorra | AND | 2015 | 38885.548589 |
| 589 | Andorra | AND | 2014 | 45680.546941 |
| 590 | Andorra | AND | 2013 | 44747.761156 |
| 591 | Andorra | AND | 2012 | 44902.387712 |
| 592 | Andorra | AND | 2011 | 51428.189700 |
| 593 | Andorra | AND | 2010 | 48237.890541 |
| 594 | Angola | AGO | 2020 | 1450.905112 |
| 595 | Angola | AGO | 2019 | 2191.347764 |
| 596 | Angola | AGO | 2018 | 2540.508878 |
| 597 | Angola | AGO | 2017 | 2439.374441 |
| 598 | Angola | AGO | 2016 | 1809.709377 |
| 599 | Angola | AGO | 2015 | 3217.339244 |
| 600 | Angola | AGO | 2014 | 5011.984412 |
| 601 | Angola | AGO | 2013 | 5061.349240 |
| 602 | Angola | AGO | 2012 | 5083.826851 |
| 603 | Angola | AGO | 2011 | 4608.155166 |
| 604 | Angola | AGO | 2010 | 3586.663680 |
| 605 | Antigua and Barbuda | ATG | 2020 | 15224.858589 |
| 606 | Antigua and Barbuda | ATG | 2019 | 18730.004797 |
| 607 | Antigua and Barbuda | ATG | 2018 | 18133.822601 |
| 608 | Antigua and Barbuda | ATG | 2017 | 16803.870234 |
| 609 | Antigua and Barbuda | ATG | 2016 | 16449.059147 |
| 610 | Antigua and Barbuda | ATG | 2015 | 15985.541139 |
| 611 | Antigua and Barbuda | ATG | 2014 | 15451.495244 |
| 612 | Antigua and Barbuda | ATG | 2013 | 14977.071832 |
| 613 | Antigua and Barbuda | ATG | 2012 | 15136.841109 |
| 614 | Antigua and Barbuda | ATG | 2011 | 14774.032181 |
| 615 | Antigua and Barbuda | ATG | 2010 | 13404.516016 |
| 616 | Argentina | ARG | 2020 | 8500.837939 |
| 617 | Argentina | ARG | 2019 | 9963.674162 |
| 618 | Argentina | ARG | 2018 | 11795.162745 |
| 619 | Argentina | ARG | 2017 | 14613.035649 |
| 620 | Argentina | ARG | 2016 | 12790.264140 |
| 621 | Argentina | ARG | 2015 | 13789.060425 |
| 622 | Argentina | ARG | 2014 | 12334.798245 |
| 623 | Argentina | ARG | 2013 | 13080.254732 |
| 624 | Argentina | ARG | 2012 | 13082.664326 |
| 625 | Argentina | ARG | 2011 | 12848.739151 |
| 626 | Argentina | ARG | 2010 | 10385.964432 |
| 627 | Armenia | ARM | 2020 | 4505.867742 |
| 628 | Armenia | ARM | 2019 | 4828.504886 |
| 629 | Armenia | ARM | 2018 | 4391.923270 |
| 630 | Armenia | ARM | 2017 | 4041.995071 |
| 631 | Armenia | ARM | 2016 | 3679.952347 |
| 632 | Armenia | ARM | 2015 | 3666.141822 |
| 633 | Armenia | ARM | 2014 | 4017.229914 |
| 634 | Armenia | ARM | 2013 | 3833.157074 |
| 635 | Armenia | ARM | 2012 | 3643.715401 |
| 636 | Armenia | ARM | 2011 | 3462.681778 |
| 637 | Armenia | ARM | 2010 | 3143.029480 |
| 638 | Aruba | ABW | 2020 | 24008.127822 |
| 639 | Aruba | ABW | 2019 | 31902.809818 |
| 640 | Aruba | ABW | 2018 | 30918.483584 |
| 641 | Aruba | ABW | 2017 | 29329.081747 |
| 642 | Aruba | ABW | 2016 | 28449.712946 |
| 643 | Aruba | ABW | 2015 | 28419.264534 |
| 644 | Aruba | ABW | 2014 | 26940.264114 |
| 645 | Aruba | ABW | 2013 | 26514.868980 |
| 646 | Aruba | ABW | 2012 | 25611.175767 |
| 647 | Aruba | ABW | 2011 | 26043.156325 |
| 648 | Aruba | ABW | 2010 | 24452.588739 |
| 649 | Australia | AUS | 2020 | 51868.247557 |
| 650 | Australia | AUS | 2019 | 55049.571920 |
| 651 | Australia | AUS | 2018 | 57273.520475 |
| 652 | Australia | AUS | 2017 | 53954.553495 |
| 653 | Australia | AUS | 2016 | 49918.793933 |
| 654 | Australia | AUS | 2015 | 56758.869203 |
| 655 | Australia | AUS | 2014 | 62558.243879 |
| 656 | Australia | AUS | 2013 | 68198.419345 |
| 657 | Australia | AUS | 2012 | 68078.044228 |
| 658 | Australia | AUS | 2011 | 62609.660716 |
| 659 | Australia | AUS | 2010 | 52147.024194 |
| 660 | Austria | AUT | 2020 | 48789.497850 |
| 661 | Austria | AUT | 2019 | 50067.585727 |
| 662 | Austria | AUT | 2018 | 51466.556563 |
| 663 | Austria | AUT | 2017 | 47429.158456 |
| 664 | Austria | AUT | 2016 | 45307.587862 |
| 665 | Austria | AUT | 2015 | 44195.817595 |
| 666 | Austria | AUT | 2014 | 51786.377175 |
| 667 | Austria | AUT | 2013 | 50731.127254 |
| 668 | Austria | AUT | 2012 | 48564.917335 |
| 669 | Austria | AUT | 2011 | 51442.276246 |
| 670 | Austria | AUT | 2010 | 46903.761585 |
| 671 | Azerbaijan | AZE | 2020 | 4229.910649 |
| 672 | Azerbaijan | AZE | 2019 | 4805.753718 |
| 673 | Azerbaijan | AZE | 2018 | 4739.794312 |
| 674 | Azerbaijan | AZE | 2017 | 4147.198142 |
| 675 | Azerbaijan | AZE | 2016 | 3880.685228 |
| 676 | Azerbaijan | AZE | 2015 | 5500.503646 |
| 677 | Azerbaijan | AZE | 2014 | 7890.840281 |
| 678 | Azerbaijan | AZE | 2013 | 7875.345367 |
| 679 | Azerbaijan | AZE | 2012 | 7495.865277 |
| 680 | Azerbaijan | AZE | 2011 | 7189.818692 |
| 681 | Azerbaijan | AZE | 2010 | 5843.533768 |
| 682 | Bahamas, The | BHS | 2020 | 23998.268019 |
| 683 | Bahamas, The | BHS | 2019 | 32279.011363 |
| 684 | Bahamas, The | BHS | 2018 | 31483.978841 |
| 685 | Bahamas, The | BHS | 2017 | 30708.987018 |
| 686 | Bahamas, The | BHS | 2016 | 29675.535891 |
| 687 | Bahamas, The | BHS | 2015 | 29724.953336 |
| 688 | Bahamas, The | BHS | 2014 | 28203.355682 |
| 689 | Bahamas, The | BHS | 2013 | 26955.788928 |
| 690 | Bahamas, The | BHS | 2012 | 28059.393657 |
| 691 | Bahamas, The | BHS | 2011 | 26644.926578 |
| 692 | Bahamas, The | BHS | 2010 | 27046.657665 |
| 693 | Bahrain | BHR | 2020 | 23433.187236 |
| 694 | Bahrain | BHR | 2019 | 25869.112913 |
| 695 | Bahrain | BHR | 2018 | 25415.846625 |
| 696 | Bahrain | BHR | 2017 | 24349.909870 |
| 697 | Bahrain | BHR | 2016 | 22867.181120 |
| 698 | Bahrain | BHR | 2015 | 22795.448858 |
| 699 | Bahrain | BHR | 2014 | 25464.760098 |
| 700 | Bahrain | BHR | 2013 | 25790.730312 |
| 701 | Bahrain | BHR | 2012 | 25102.726349 |
| 702 | Bahrain | BHR | 2011 | 23741.557463 |
| 703 | Bahrain | BHR | 2010 | 21186.814329 |
| 704 | Bangladesh | BGD | 2020 | 2233.305901 |
| 705 | Bangladesh | BGD | 2019 | 2122.078397 |
| 706 | Bangladesh | BGD | 2018 | 1963.412492 |
| 707 | Bangladesh | BGD | 2017 | 1815.610262 |
| 708 | Bangladesh | BGD | 2016 | 1659.962496 |
| 709 | Bangladesh | BGD | 2015 | 1236.004392 |
| 710 | Bangladesh | BGD | 2014 | 1108.514957 |
| 711 | Bangladesh | BGD | 2013 | 973.773904 |
| 712 | Bangladesh | BGD | 2012 | 876.818010 |
| 713 | Bangladesh | BGD | 2011 | 856.381887 |
| 714 | Bangladesh | BGD | 2010 | 776.859577 |
| 715 | Barbados | BRB | 2020 | 16882.501523 |
| 716 | Barbados | BRB | 2019 | 19063.102291 |
| 717 | Barbados | BRB | 2018 | 18271.252253 |
| 718 | Barbados | BRB | 2017 | 17881.563253 |
| 719 | Barbados | BRB | 2016 | 17381.365087 |
| 720 | Barbados | BRB | 2015 | 17023.694365 |
| 721 | Barbados | BRB | 2014 | 16964.752264 |
| 722 | Barbados | BRB | 2013 | 16923.590920 |
| 723 | Barbados | BRB | 2012 | 16704.924384 |
| 724 | Barbados | BRB | 2011 | 16902.492323 |
| 725 | Barbados | BRB | 2010 | 16494.243041 |
| 726 | Belarus | BLR | 2020 | 6542.864540 |
| 727 | Belarus | BLR | 2019 | 6837.768321 |
| 728 | Belarus | BLR | 2018 | 6360.053101 |
| 729 | Belarus | BLR | 2017 | 5785.533977 |
| 730 | Belarus | BLR | 2016 | 5039.775609 |
| 731 | Belarus | BLR | 2015 | 5967.068560 |
| 732 | Belarus | BLR | 2014 | 8341.290143 |
| 733 | Belarus | BLR | 2013 | 7998.080205 |
| 734 | Belarus | BLR | 2012 | 6953.215917 |
| 735 | Belarus | BLR | 2011 | 6527.659343 |
| 736 | Belarus | BLR | 2010 | 6034.678852 |
| 737 | Belgium | BEL | 2020 | 45609.003494 |
| 738 | Belgium | BEL | 2019 | 46641.721402 |
| 739 | Belgium | BEL | 2018 | 47544.981147 |
| 740 | Belgium | BEL | 2017 | 44198.482391 |
| 741 | Belgium | BEL | 2016 | 42012.622719 |
| 742 | Belgium | BEL | 2015 | 41008.296719 |
| 743 | Belgium | BEL | 2014 | 47764.071512 |
| 744 | Belgium | BEL | 2013 | 46757.951856 |
| 745 | Belgium | BEL | 2012 | 44670.560685 |
| 746 | Belgium | BEL | 2011 | 47410.566928 |
| 747 | Belgium | BEL | 2010 | 44184.946354 |
| 748 | Belize | BLZ | 2020 | 5185.158070 |
| 749 | Belize | BLZ | 2019 | 6134.215233 |
| 750 | Belize | BLZ | 2018 | 6001.024262 |
| 751 | Belize | BLZ | 2017 | 6049.391948 |
| 752 | Belize | BLZ | 2016 | 6099.957102 |
| 753 | Belize | BLZ | 2015 | 6098.600080 |
| 754 | Belize | BLZ | 2014 | 6031.548402 |
| 755 | Belize | BLZ | 2013 | 5865.470902 |
| 756 | Belize | BLZ | 2012 | 5635.521526 |
| 757 | Belize | BLZ | 2011 | 5519.339008 |
| 758 | Belize | BLZ | 2010 | 5399.062096 |
| 759 | Benin | BEN | 2020 | 1240.733155 |
| 760 | Benin | BEN | 2019 | 1170.885995 |
| 761 | Benin | BEN | 2018 | 1194.438214 |
| 762 | Benin | BEN | 2017 | 1095.274459 |
| 763 | Benin | BEN | 2016 | 1049.820303 |
| 764 | Benin | BEN | 2015 | 1041.652523 |
| 765 | Benin | BEN | 2014 | 1251.504765 |
| 766 | Benin | BEN | 2013 | 1214.295565 |
| 767 | Benin | BEN | 2012 | 1112.569536 |
| 768 | Benin | BEN | 2011 | 1099.414311 |
| 769 | Benin | BEN | 2010 | 1009.489495 |
| 770 | Bermuda | BMU | 2020 | 107791.886435 |
| 771 | Bermuda | BMU | 2019 | 116153.166122 |
| 772 | Bermuda | BMU | 2018 | 113050.736882 |
| 773 | Bermuda | BMU | 2017 | 111820.581466 |
| 774 | Bermuda | BMU | 2016 | 106885.878489 |
| 775 | Bermuda | BMU | 2015 | 102005.625642 |
| 776 | Bermuda | BMU | 2014 | 98467.683994 |
| 777 | Bermuda | BMU | 2013 | 99471.638898 |
| 778 | Bermuda | BMU | 2012 | 98431.865181 |
| 779 | Bermuda | BMU | 2011 | 97774.162072 |
| 780 | Bermuda | BMU | 2010 | 101875.284073 |
| 781 | Bhutan | BTN | 2020 | 3181.339747 |
| 782 | Bhutan | BTN | 2019 | 3564.598772 |
| 783 | Bhutan | BTN | 2018 | 3389.777303 |
| 784 | Bhutan | BTN | 2017 | 3427.173845 |
| 785 | Bhutan | BTN | 2016 | 2879.546564 |
| 786 | Bhutan | BTN | 2015 | 2695.636924 |
| 787 | Bhutan | BTN | 2014 | 2589.899160 |
| 788 | Bhutan | BTN | 2013 | 2409.440006 |
| 789 | Bhutan | BTN | 2012 | 2470.072151 |
| 790 | Bhutan | BTN | 2011 | 2491.273439 |
| 791 | Bhutan | BTN | 2010 | 2194.125876 |
| 792 | Bolivia | BOL | 2020 | 3068.812555 |
| 793 | Bolivia | BOL | 2019 | 3472.380831 |
| 794 | Bolivia | BOL | 2018 | 3471.006951 |
| 795 | Bolivia | BOL | 2017 | 3280.008214 |
| 796 | Bolivia | BOL | 2016 | 3013.502707 |
| 797 | Bolivia | BOL | 2015 | 2975.648811 |
| 798 | Bolivia | BOL | 2014 | 3022.462884 |
| 799 | Bolivia | BOL | 2013 | 2853.797162 |
| 800 | Bolivia | BOL | 2012 | 2562.466784 |
| 801 | Bolivia | BOL | 2011 | 2304.982462 |
| 802 | Bolivia | BOL | 2010 | 1922.058571 |
| 803 | Bosnia and Herzegovina | BIH | 2020 | 6095.104237 |
| 804 | Bosnia and Herzegovina | BIH | 2019 | 6094.724823 |
| 805 | Bosnia and Herzegovina | BIH | 2018 | 6024.493150 |
| 806 | Bosnia and Herzegovina | BIH | 2017 | 5327.392304 |
| 807 | Bosnia and Herzegovina | BIH | 2016 | 4917.263766 |
| 808 | Bosnia and Herzegovina | BIH | 2015 | 4654.608620 |
| 809 | Bosnia and Herzegovina | BIH | 2014 | 5196.970084 |
| 810 | Bosnia and Herzegovina | BIH | 2013 | 5025.241753 |
| 811 | Bosnia and Herzegovina | BIH | 2012 | 4688.345823 |
| 812 | Bosnia and Herzegovina | BIH | 2011 | 4980.904688 |
| 813 | Bosnia and Herzegovina | BIH | 2010 | 4506.932352 |
| 814 | Botswana | BWA | 2020 | 5875.070606 |
| 815 | Botswana | BWA | 2019 | 6691.161053 |
| 816 | Botswana | BWA | 2018 | 6947.817841 |
| 817 | Botswana | BWA | 2017 | 6705.341062 |
| 818 | Botswana | BWA | 2016 | 6411.551666 |
| 819 | Botswana | BWA | 2015 | 5869.737579 |
| 820 | Botswana | BWA | 2014 | 6844.033250 |
| 821 | Botswana | BWA | 2013 | 6436.603319 |
| 822 | Botswana | BWA | 2012 | 6392.987347 |
| 823 | Botswana | BWA | 2011 | 7080.778643 |
| 824 | Botswana | BWA | 2010 | 6041.732051 |
| 825 | Brazil | BRA | 2020 | 6923.699912 |
| 826 | Brazil | BRA | 2019 | 8845.324149 |
| 827 | Brazil | BRA | 2018 | 9121.020995 |
| 828 | Brazil | BRA | 2017 | 9896.718895 |
| 829 | Brazil | BRA | 2016 | 8680.736469 |
| 830 | Brazil | BRA | 2015 | 8783.215424 |
| 831 | Brazil | BRA | 2014 | 12071.404464 |
| 832 | Brazil | BRA | 2013 | 12258.565709 |
| 833 | Brazil | BRA | 2012 | 12327.513101 |
| 834 | Brazil | BRA | 2011 | 13200.556235 |
| 835 | Brazil | BRA | 2010 | 11249.291890 |
| 836 | British Virgin Islands | VGB | 2020 | NaN |
| 837 | British Virgin Islands | VGB | 2019 | NaN |
| 838 | British Virgin Islands | VGB | 2018 | NaN |
| 839 | British Virgin Islands | VGB | 2017 | NaN |
| 840 | British Virgin Islands | VGB | 2016 | NaN |
| 841 | British Virgin Islands | VGB | 2015 | NaN |
| 842 | British Virgin Islands | VGB | 2014 | NaN |
| 843 | British Virgin Islands | VGB | 2013 | NaN |
| 844 | British Virgin Islands | VGB | 2012 | NaN |
| 845 | British Virgin Islands | VGB | 2011 | NaN |
| 846 | British Virgin Islands | VGB | 2010 | NaN |
| 847 | Brunei Darussalam | BRN | 2020 | 27179.352887 |
| 848 | Brunei Darussalam | BRN | 2019 | 30748.309237 |
| 849 | Brunei Darussalam | BRN | 2018 | 31240.501789 |
| 850 | Brunei Darussalam | BRN | 2017 | 28186.986735 |
| 851 | Brunei Darussalam | BRN | 2016 | 26762.035044 |
| 852 | Brunei Darussalam | BRN | 2015 | 30681.433970 |
| 853 | Brunei Darussalam | BRN | 2014 | 41035.777123 |
| 854 | Brunei Darussalam | BRN | 2013 | 43950.045462 |
| 855 | Brunei Darussalam | BRN | 2012 | 46844.197339 |
| 856 | Brunei Darussalam | BRN | 2011 | 46139.107576 |
| 857 | Brunei Darussalam | BRN | 2010 | 34609.711983 |
| 858 | Bulgaria | BGR | 2020 | 10148.342395 |
| 859 | Bulgaria | BGR | 2019 | 9874.336326 |
| 860 | Bulgaria | BGR | 2018 | 9447.655897 |
| 861 | Bulgaria | BGR | 2017 | 8381.881346 |
| 862 | Bulgaria | BGR | 2016 | 7570.931655 |
| 863 | Bulgaria | BGR | 2015 | 7078.860323 |
| 864 | Bulgaria | BGR | 2014 | 7912.274844 |
| 865 | Bulgaria | BGR | 2013 | 7687.713682 |
| 866 | Bulgaria | BGR | 2012 | 7430.737380 |
| 867 | Bulgaria | BGR | 2011 | 7857.167070 |
| 868 | Bulgaria | BGR | 2010 | 6863.667068 |
| 869 | Burkina Faso | BFA | 2020 | 823.552411 |
| 870 | Burkina Faso | BFA | 2019 | 765.229560 |
| 871 | Burkina Faso | BFA | 2018 | 779.202769 |
| 872 | Burkina Faso | BFA | 2017 | 711.184543 |
| 873 | Burkina Faso | BFA | 2016 | 665.786329 |
| 874 | Burkina Faso | BFA | 2015 | 632.126686 |
| 875 | Burkina Faso | BFA | 2014 | 767.371344 |
| 876 | Burkina Faso | BFA | 2013 | 762.303780 |
| 877 | Burkina Faso | BFA | 2012 | 733.972880 |
| 878 | Burkina Faso | BFA | 2011 | 727.612475 |
| 879 | Burkina Faso | BFA | 2010 | 627.270396 |
| 880 | Burundi | BDI | 2020 | 216.827417 |
| 881 | Burundi | BDI | 2019 | 216.972971 |
| 882 | Burundi | BDI | 2018 | 232.060617 |
| 883 | Burundi | BDI | 2017 | 244.145422 |
| 884 | Burundi | BDI | 2016 | 242.539527 |
| 885 | Burundi | BDI | 2015 | 289.359627 |
| 886 | Burundi | BDI | 2014 | 257.818557 |
| 887 | Burundi | BDI | 2013 | 241.547666 |
| 888 | Burundi | BDI | 2012 | 238.205945 |
| 889 | Burundi | BDI | 2011 | 236.451347 |
| 890 | Burundi | BDI | 2010 | 222.660583 |
| 891 | Cabo Verde | CPV | 2020 | 3126.399859 |
| 892 | Cabo Verde | CPV | 2019 | 3903.050317 |
| 893 | Cabo Verde | CPV | 2018 | 3860.454808 |
| 894 | Cabo Verde | CPV | 2017 | 3534.343575 |
| 895 | Cabo Verde | CPV | 2016 | 3312.696745 |
| 896 | Cabo Verde | CPV | 2015 | 3169.078901 |
| 897 | Cabo Verde | CPV | 2014 | 3739.278279 |
| 898 | Cabo Verde | CPV | 2013 | 3757.659953 |
| 899 | Cabo Verde | CPV | 2012 | 3583.461725 |
| 900 | Cabo Verde | CPV | 2011 | 3880.069205 |
| 901 | Cabo Verde | CPV | 2010 | 3500.977468 |
| 902 | Cambodia | KHM | 2020 | 1577.911740 |
| 903 | Cambodia | KHM | 2019 | 1671.385400 |
| 904 | Cambodia | KHM | 2018 | 1533.315985 |
| 905 | Cambodia | KHM | 2017 | 1400.899265 |
| 906 | Cambodia | KHM | 2016 | 1281.105971 |
| 907 | Cambodia | KHM | 2015 | 1170.742816 |
| 908 | Cambodia | KHM | 2014 | 1098.074538 |
| 909 | Cambodia | KHM | 2013 | 1015.220881 |
| 910 | Cambodia | KHM | 2012 | 950.482545 |
| 911 | Cambodia | KHM | 2011 | 880.310304 |
| 912 | Cambodia | KHM | 2010 | 782.695739 |
| 913 | Cameroon | CMR | 2020 | 1539.130545 |
| 914 | Cameroon | CMR | 2019 | 1538.687912 |
| 915 | Cameroon | CMR | 2018 | 1594.060110 |
| 916 | Cameroon | CMR | 2017 | 1479.862222 |
| 917 | Cameroon | CMR | 2016 | 1426.065481 |
| 918 | Cameroon | CMR | 2015 | 1399.675336 |
| 919 | Cameroon | CMR | 2014 | 1631.713985 |
| 920 | Cameroon | CMR | 2013 | 1559.139049 |
| 921 | Cameroon | CMR | 2012 | 1433.723928 |
| 922 | Cameroon | CMR | 2011 | 1497.926585 |
| 923 | Cameroon | CMR | 2010 | 1383.813865 |
| 924 | Canada | CAN | 2020 | 43562.435831 |
| 925 | Canada | CAN | 2019 | 46374.152752 |
| 926 | Canada | CAN | 2018 | 46548.638411 |
| 927 | Canada | CAN | 2017 | 45129.429298 |
| 928 | Canada | CAN | 2016 | 42315.603706 |
| 929 | Canada | CAN | 2015 | 43596.135537 |
| 930 | Canada | CAN | 2014 | 50955.998323 |
| 931 | Canada | CAN | 2013 | 52635.174958 |
| 932 | Canada | CAN | 2012 | 52669.089963 |
| 933 | Canada | CAN | 2011 | 52223.696112 |
| 934 | Canada | CAN | 2010 | 47562.083425 |
| 935 | Cayman Islands | CYM | 2020 | 83897.505443 |
| 936 | Cayman Islands | CYM | 2019 | 89846.321220 |
| 937 | Cayman Islands | CYM | 2018 | 85231.774254 |
| 938 | Cayman Islands | CYM | 2017 | 81255.112457 |
| 939 | Cayman Islands | CYM | 2016 | 78858.280255 |
| 940 | Cayman Islands | CYM | 2015 | 77295.845293 |
| 941 | Cayman Islands | CYM | 2014 | 76610.648456 |
| 942 | Cayman Islands | CYM | 2013 | 75685.357369 |
| 943 | Cayman Islands | CYM | 2012 | 75466.136546 |
| 944 | Cayman Islands | CYM | 2011 | 75435.614220 |
| 945 | Cayman Islands | CYM | 2010 | 76873.194278 |
| 946 | Central African Republic | CAF | 2020 | 435.469248 |
| 947 | Central African Republic | CAF | 2019 | 426.408753 |
| 948 | Central African Republic | CAF | 2018 | 435.932297 |
| 949 | Central African Republic | CAF | 2017 | 414.740322 |
| 950 | Central African Republic | CAF | 2016 | 372.135456 |
| 951 | Central African Republic | CAF | 2015 | 351.879755 |
| 952 | Central African Republic | CAF | 2014 | 394.856933 |
| 953 | Central African Republic | CAF | 2013 | 352.226855 |
| 954 | Central African Republic | CAF | 2012 | 525.867504 |
| 955 | Central African Republic | CAF | 2011 | 515.209503 |
| 956 | Central African Republic | CAF | 2010 | 459.776982 |
| 957 | Chad | TCD | 2020 | 643.772216 |
| 958 | Chad | TCD | 2019 | 701.621201 |
| 959 | Chad | TCD | 2018 | 720.265101 |
| 960 | Chad | TCD | 2017 | 662.897473 |
| 961 | Chad | TCD | 2016 | 691.980077 |
| 962 | Chad | TCD | 2015 | 774.411603 |
| 963 | Chad | TCD | 2014 | 1017.787762 |
| 964 | Chad | TCD | 2013 | 980.083544 |
| 965 | Chad | TCD | 2012 | 969.616143 |
| 966 | Chad | TCD | 2011 | 988.194160 |
| 967 | Chad | TCD | 2010 | 896.876705 |
| 968 | Channel Islands | CHI | 2020 | 57339.526871 |
| 969 | Channel Islands | CHI | 2019 | 61281.327225 |
| 970 | Channel Islands | CHI | 2018 | 62316.219949 |
| 971 | Channel Islands | CHI | 2017 | 57683.893897 |
| 972 | Channel Islands | CHI | 2016 | 58093.996063 |
| 973 | Channel Islands | CHI | 2015 | NaN |
| 974 | Channel Islands | CHI | 2014 | NaN |
| 975 | Channel Islands | CHI | 2013 | NaN |
| 976 | Channel Islands | CHI | 2012 | NaN |
| 977 | Channel Islands | CHI | 2011 | NaN |
| 978 | Channel Islands | CHI | 2010 | NaN |
| 979 | Chile | CHL | 2020 | 13173.784794 |
| 980 | Chile | CHL | 2019 | 14632.690308 |
| 981 | Chile | CHL | 2018 | 15820.033357 |
| 982 | Chile | CHL | 2017 | 15034.058425 |
| 983 | Chile | CHL | 2016 | 13788.240016 |
| 984 | Chile | CHL | 2015 | 13567.357217 |
| 985 | Chile | CHL | 2014 | 14675.150873 |
| 986 | Chile | CHL | 2013 | 15842.159157 |
| 987 | Chile | CHL | 2012 | 15397.780460 |
| 988 | Chile | CHL | 2011 | 14637.756167 |
| 989 | Chile | CHL | 2010 | 12764.593118 |
| 990 | China | CHN | 2020 | 10408.719554 |
| 991 | China | CHN | 2019 | 10143.860221 |
| 992 | China | CHN | 2018 | 9905.406383 |
| 993 | China | CHN | 2017 | 8817.045608 |
| 994 | China | CHN | 2016 | 8094.390167 |
| 995 | China | CHN | 2015 | 8016.445595 |
| 996 | China | CHN | 2014 | 7636.074340 |
| 997 | China | CHN | 2013 | 7020.386074 |
| 998 | China | CHN | 2012 | 6300.582180 |
| 999 | China | CHN | 2011 | 5614.386022 |
| 1000 | China | CHN | 2010 | 4550.473944 |
| 1001 | Colombia | COL | 2020 | 5304.289129 |
| 1002 | Colombia | COL | 2019 | 6436.509215 |
| 1003 | Colombia | COL | 2018 | 6782.037920 |
| 1004 | Colombia | COL | 2017 | 6449.970987 |
| 1005 | Colombia | COL | 2016 | 5936.261022 |
| 1006 | Colombia | COL | 2015 | 6228.651622 |
| 1007 | Colombia | COL | 2014 | 8167.472842 |
| 1008 | Colombia | COL | 2013 | 8263.641929 |
| 1009 | Colombia | COL | 2012 | 8096.801510 |
| 1010 | Colombia | COL | 2011 | 7392.943600 |
| 1011 | Colombia | COL | 2010 | 6392.758026 |
| 1012 | Comoros | COM | 2020 | 1519.586780 |
| 1013 | Comoros | COM | 2019 | 1510.797323 |
| 1014 | Comoros | COM | 2018 | 1531.337811 |
| 1015 | Comoros | COM | 2017 | 1414.586689 |
| 1016 | Comoros | COM | 2016 | 1357.266229 |
| 1017 | Comoros | COM | 2015 | 1322.936775 |
| 1018 | Comoros | COM | 2014 | 1608.687875 |
| 1019 | Comoros | COM | 2013 | 1595.989819 |
| 1020 | Comoros | COM | 2012 | 1483.951559 |
| 1021 | Comoros | COM | 2011 | 1526.832638 |
| 1022 | Comoros | COM | 2010 | 1384.063284 |
| 1023 | Congo, Dem. Rep. | COD | 2020 | 524.666686 |
| 1024 | Congo, Dem. Rep. | COD | 2019 | 575.882781 |
| 1025 | Congo, Dem. Rep. | COD | 2018 | 546.212593 |
| 1026 | Congo, Dem. Rep. | COD | 2017 | 451.089089 |
| 1027 | Congo, Dem. Rep. | COD | 2016 | 456.027951 |
| 1028 | Congo, Dem. Rep. | COD | 2015 | 482.064569 |
| 1029 | Congo, Dem. Rep. | COD | 2014 | 472.266236 |
| 1030 | Congo, Dem. Rep. | COD | 2013 | 444.864358 |
| 1031 | Congo, Dem. Rep. | COD | 2012 | 412.776261 |
| 1032 | Congo, Dem. Rep. | COD | 2011 | 376.374981 |
| 1033 | Congo, Dem. Rep. | COD | 2010 | 324.827726 |
| 1034 | Congo, Rep. | COG | 2020 | 2011.269479 |
| 1035 | Congo, Rep. | COG | 2019 | 2508.944783 |
| 1036 | Congo, Rep. | COG | 2018 | 2715.243105 |
| 1037 | Congo, Rep. | COG | 2017 | 2227.720139 |
| 1038 | Congo, Rep. | COG | 2016 | 2107.503024 |
| 1039 | Congo, Rep. | COG | 2015 | 2455.347910 |
| 1040 | Congo, Rep. | COG | 2014 | 3623.807460 |
| 1041 | Congo, Rep. | COG | 2013 | 3719.651036 |
| 1042 | Congo, Rep. | COG | 2012 | 3753.860928 |
| 1043 | Congo, Rep. | COG | 2011 | 3415.062374 |
| 1044 | Congo, Rep. | COG | 2010 | 2962.762481 |
| 1045 | Costa Rica | CRI | 2020 | 12179.256674 |
| 1046 | Costa Rica | CRI | 2019 | 12669.341155 |
| 1047 | Costa Rica | CRI | 2018 | 12383.149952 |
| 1048 | Costa Rica | CRI | 2017 | 12118.133625 |
| 1049 | Costa Rica | CRI | 2016 | 11899.813983 |
| 1050 | Costa Rica | CRI | 2015 | 11529.955173 |
| 1051 | Costa Rica | CRI | 2014 | 10737.678881 |
| 1052 | Costa Rica | CRI | 2013 | 10633.266550 |
| 1053 | Costa Rica | CRI | 2012 | 9971.651656 |
| 1054 | Costa Rica | CRI | 2011 | 9137.455101 |
| 1055 | Costa Rica | CRI | 2010 | 8147.243985 |
| 1056 | Cote d'Ivoire | CIV | 2020 | 2349.069882 |
| 1057 | Cote d'Ivoire | CIV | 2019 | 2290.787379 |
| 1058 | Cote d'Ivoire | CIV | 2018 | 2295.540335 |
| 1059 | Cote d'Ivoire | CIV | 2017 | 2113.341525 |
| 1060 | Cote d'Ivoire | CIV | 2016 | 1999.195372 |
| 1061 | Cote d'Ivoire | CIV | 2015 | 1941.581898 |
| 1062 | Cote d'Ivoire | CIV | 2014 | 2124.019430 |
| 1063 | Cote d'Ivoire | CIV | 2013 | 1903.054229 |
| 1064 | Cote d'Ivoire | CIV | 2012 | 1649.301615 |
| 1065 | Cote d'Ivoire | CIV | 2011 | 1701.704641 |
| 1066 | Cote d'Ivoire | CIV | 2010 | 1654.177959 |
| 1067 | Croatia | HRV | 2020 | 14269.908855 |
| 1068 | Croatia | HRV | 2019 | 15120.902903 |
| 1069 | Croatia | HRV | 2018 | 15040.036918 |
| 1070 | Croatia | HRV | 2017 | 13592.254524 |
| 1071 | Croatia | HRV | 2016 | 12579.922703 |
| 1072 | Croatia | HRV | 2015 | 12098.512025 |
| 1073 | Croatia | HRV | 2014 | 14001.160344 |
| 1074 | Croatia | HRV | 2013 | 13979.185560 |
| 1075 | Croatia | HRV | 2012 | 13439.664556 |
| 1076 | Croatia | HRV | 2011 | 14655.874388 |
| 1077 | Croatia | HRV | 2010 | 13693.500029 |
| 1078 | Cuba | CUB | 2020 | 9499.572504 |
| 1079 | Cuba | CUB | 2019 | 9139.380510 |
| 1080 | Cuba | CUB | 2018 | 8831.910409 |
| 1081 | Cuba | CUB | 2017 | 8543.330067 |
| 1082 | Cuba | CUB | 2016 | 8055.925868 |
| 1083 | Cuba | CUB | 2015 | 7683.740254 |
| 1084 | Cuba | CUB | 2014 | 7117.535735 |
| 1085 | Cuba | CUB | 2013 | 6814.243844 |
| 1086 | Cuba | CUB | 2012 | 6467.337914 |
| 1087 | Cuba | CUB | 2011 | 6106.006792 |
| 1088 | Cuba | CUB | 2010 | 5275.532601 |
| 1089 | Curacao | CUW | 2020 | 16356.093325 |
| 1090 | Curacao | CUW | 2019 | 19220.686579 |
| 1091 | Curacao | CUW | 2018 | 19119.124489 |
| 1092 | Curacao | CUW | 2017 | 18938.244097 |
| 1093 | Curacao | CUW | 2016 | 18944.096277 |
| 1094 | Curacao | CUW | 2015 | 19361.812963 |
| 1095 | Curacao | CUW | 2014 | 19623.030071 |
| 1096 | Curacao | CUW | 2013 | 19721.292183 |
| 1097 | Curacao | CUW | 2012 | 19809.822317 |
| 1098 | Curacao | CUW | 2011 | 19426.326400 |
| 1099 | Curacao | CUW | 2010 | NaN |
| 1100 | Cyprus | CYP | 2020 | 28281.425781 |
| 1101 | Cyprus | CYP | 2019 | 29420.000000 |
| 1102 | Cyprus | CYP | 2018 | 29335.046875 |
| 1103 | Cyprus | CYP | 2017 | 26608.695312 |
| 1104 | Cyprus | CYP | 2016 | 24605.349609 |
| 1105 | Cyprus | CYP | 2015 | 23408.441406 |
| 1106 | Cyprus | CYP | 2014 | 27162.322266 |
| 1107 | Cyprus | CYP | 2013 | 27727.535156 |
| 1108 | Cyprus | CYP | 2012 | 28910.746094 |
| 1109 | Cyprus | CYP | 2011 | 32395.753906 |
| 1110 | Cyprus | CYP | 2010 | 31023.267578 |
| 1111 | Czechia | CZE | 2020 | 22992.879383 |
| 1112 | Czechia | CZE | 2019 | 23664.847863 |
| 1113 | Czechia | CZE | 2018 | 23424.480460 |
| 1114 | Czechia | CZE | 2017 | 20636.199952 |
| 1115 | Czechia | CZE | 2016 | 18575.232027 |
| 1116 | Czechia | CZE | 2015 | 17829.698322 |
| 1117 | Czechia | CZE | 2014 | 19890.919906 |
| 1118 | Czechia | CZE | 2013 | 20133.169143 |
| 1119 | Czechia | CZE | 2012 | 19870.801212 |
| 1120 | Czechia | CZE | 2011 | 21871.266075 |
| 1121 | Czechia | CZE | 2010 | 19960.068487 |
| 1122 | Denmark | DNK | 2020 | 60836.592412 |
| 1123 | Denmark | DNK | 2019 | 59592.980689 |
| 1124 | Denmark | DNK | 2018 | 61591.928870 |
| 1125 | Denmark | DNK | 2017 | 57610.098180 |
| 1126 | Denmark | DNK | 2016 | 54663.998372 |
| 1127 | Denmark | DNK | 2015 | 53254.856370 |
| 1128 | Denmark | DNK | 2014 | 62548.984733 |
| 1129 | Denmark | DNK | 2013 | 61191.193704 |
| 1130 | Denmark | DNK | 2012 | 58507.508052 |
| 1131 | Denmark | DNK | 2011 | 61753.647132 |
| 1132 | Denmark | DNK | 2010 | 58041.398436 |
| 1133 | Djibouti | DJI | 2020 | 2921.738706 |
| 1134 | Djibouti | DJI | 2019 | 2876.043664 |
| 1135 | Djibouti | DJI | 2018 | 2755.838293 |
| 1136 | Djibouti | DJI | 2017 | 2655.733220 |
| 1137 | Djibouti | DJI | 2016 | 2545.738799 |
| 1138 | Djibouti | DJI | 2015 | 2409.311902 |
| 1139 | Djibouti | DJI | 2014 | 2239.114538 |
| 1140 | Djibouti | DJI | 2013 | 2102.197948 |
| 1141 | Djibouti | DJI | 2012 | 1418.460858 |
| 1142 | Djibouti | DJI | 2011 | 1322.726251 |
| 1143 | Djibouti | DJI | 2010 | 1227.820853 |
| 1144 | Dominica | DMA | 2020 | 7003.469891 |
| 1145 | Dominica | DMA | 2019 | 8561.587011 |
| 1146 | Dominica | DMA | 2018 | 7833.195013 |
| 1147 | Dominica | DMA | 2017 | 7408.091301 |
| 1148 | Dominica | DMA | 2016 | 8223.041450 |
| 1149 | Dominica | DMA | 2015 | 7724.042411 |
| 1150 | Dominica | DMA | 2014 | 7502.120910 |
| 1151 | Dominica | DMA | 2013 | 7240.679119 |
| 1152 | Dominica | DMA | 2012 | 7054.875977 |
| 1153 | Dominica | DMA | 2011 | 7288.497948 |
| 1154 | Dominica | DMA | 2010 | 7182.400203 |
| 1155 | Dominican Republic | DOM | 2020 | 7167.914974 |
| 1156 | Dominican Republic | DOM | 2019 | 8173.344699 |
| 1157 | Dominican Republic | DOM | 2018 | 7947.159331 |
| 1158 | Dominican Republic | DOM | 2017 | 7513.497982 |
| 1159 | Dominican Republic | DOM | 2016 | 7191.069703 |
| 1160 | Dominican Republic | DOM | 2015 | 6838.936746 |
| 1161 | Dominican Republic | DOM | 2014 | 6533.670911 |
| 1162 | Dominican Republic | DOM | 2013 | 6171.295127 |
| 1163 | Dominican Republic | DOM | 2012 | 6049.471587 |
| 1164 | Dominican Republic | DOM | 2011 | 5859.381524 |
| 1165 | Dominican Republic | DOM | 2010 | 5509.568034 |
| 1166 | Ecuador | ECU | 2020 | 5645.199290 |
| 1167 | Ecuador | ECU | 2019 | 6233.258167 |
| 1168 | Ecuador | ECU | 2018 | 6321.349401 |
| 1169 | Ecuador | ECU | 2017 | 6246.404252 |
| 1170 | Ecuador | ECU | 2016 | 6079.088736 |
| 1171 | Ecuador | ECU | 2015 | 6130.586676 |
| 1172 | Ecuador | ECU | 2014 | 6374.631486 |
| 1173 | Ecuador | ECU | 2013 | 6050.354611 |
| 1174 | Ecuador | ECU | 2012 | 5678.455721 |
| 1175 | Ecuador | ECU | 2011 | 5202.656459 |
| 1176 | Ecuador | ECU | 2010 | 4640.246344 |
| 1177 | Egypt, Arab Rep. | EGY | 2020 | 3571.556907 |
| 1178 | Egypt, Arab Rep. | EGY | 2019 | 3017.258336 |
| 1179 | Egypt, Arab Rep. | EGY | 2018 | 2531.200079 |
| 1180 | Egypt, Arab Rep. | EGY | 2017 | 2439.967284 |
| 1181 | Egypt, Arab Rep. | EGY | 2016 | 3331.612461 |
| 1182 | Egypt, Arab Rep. | EGY | 2015 | 3370.382447 |
| 1183 | Egypt, Arab Rep. | EGY | 2014 | 3196.861381 |
| 1184 | Egypt, Arab Rep. | EGY | 2013 | 3088.890834 |
| 1185 | Egypt, Arab Rep. | EGY | 2012 | 3059.135428 |
| 1186 | Egypt, Arab Rep. | EGY | 2011 | 2645.622535 |
| 1187 | Egypt, Arab Rep. | EGY | 2010 | 2509.772034 |
| 1188 | El Salvador | SLV | 2020 | 3961.726633 |
| 1189 | El Salvador | SLV | 2019 | 4280.288404 |
| 1190 | El Salvador | SLV | 2018 | 4145.862351 |
| 1191 | El Salvador | SLV | 2017 | 3986.049014 |
| 1192 | El Salvador | SLV | 2016 | 3870.312982 |
| 1193 | El Salvador | SLV | 2015 | 3761.513680 |
| 1194 | El Salvador | SLV | 2014 | 3638.517658 |
| 1195 | El Salvador | SLV | 2013 | 3555.162100 |
| 1196 | El Salvador | SLV | 2012 | 3471.051269 |
| 1197 | El Salvador | SLV | 2011 | 3304.974183 |
| 1198 | El Salvador | SLV | 2010 | 3017.307395 |
| 1199 | Equatorial Guinea | GNQ | 2020 | 6198.942524 |
| 1200 | Equatorial Guinea | GNQ | 2019 | 7317.390024 |
| 1201 | Equatorial Guinea | GNQ | 2018 | 8719.186870 |
| 1202 | Equatorial Guinea | GNQ | 2017 | 8410.397980 |
| 1203 | Equatorial Guinea | GNQ | 2016 | 8035.307666 |
| 1204 | Equatorial Guinea | GNQ | 2015 | 9788.983804 |
| 1205 | Equatorial Guinea | GNQ | 2014 | 16804.924927 |
| 1206 | Equatorial Guinea | GNQ | 2013 | 17644.594305 |
| 1207 | Equatorial Guinea | GNQ | 2012 | 18756.425027 |
| 1208 | Equatorial Guinea | GNQ | 2011 | 18659.416025 |
| 1209 | Equatorial Guinea | GNQ | 2010 | 14905.514576 |
| 1210 | Eritrea | ERI | 2020 | NaN |
| 1211 | Eritrea | ERI | 2019 | NaN |
| 1212 | Eritrea | ERI | 2018 | NaN |
| 1213 | Eritrea | ERI | 2017 | NaN |
| 1214 | Eritrea | ERI | 2016 | NaN |
| 1215 | Eritrea | ERI | 2015 | NaN |
| 1216 | Eritrea | ERI | 2014 | NaN |
| 1217 | Eritrea | ERI | 2013 | NaN |
| 1218 | Eritrea | ERI | 2012 | NaN |
| 1219 | Eritrea | ERI | 2011 | 643.790042 |
| 1220 | Eritrea | ERI | 2010 | 504.972460 |
| 1221 | Estonia | EST | 2020 | 23595.243684 |
| 1222 | Estonia | EST | 2019 | 23424.484707 |
| 1223 | Estonia | EST | 2018 | 23165.849479 |
| 1224 | Estonia | EST | 2017 | 20437.765377 |
| 1225 | Estonia | EST | 2016 | 18295.342932 |
| 1226 | Estonia | EST | 2015 | 17402.037613 |
| 1227 | Estonia | EST | 2014 | 20261.066730 |
| 1228 | Estonia | EST | 2013 | 19056.001923 |
| 1229 | Estonia | EST | 2012 | 17403.205325 |
| 1230 | Estonia | EST | 2011 | 17487.804783 |
| 1231 | Estonia | EST | 2010 | 14663.044613 |
| 1232 | Eswatini | SWZ | 2020 | 3372.904610 |
| 1233 | Eswatini | SWZ | 2019 | 3818.540484 |
| 1234 | Eswatini | SWZ | 2018 | 4021.445556 |
| 1235 | Eswatini | SWZ | 2017 | 3824.046783 |
| 1236 | Eswatini | SWZ | 2016 | 3339.990401 |
| 1237 | Eswatini | SWZ | 2015 | 3583.311290 |
| 1238 | Eswatini | SWZ | 2014 | 3928.522755 |
| 1239 | Eswatini | SWZ | 2013 | 4111.128382 |
| 1240 | Eswatini | SWZ | 2012 | 4396.579120 |
| 1241 | Eswatini | SWZ | 2011 | 4360.959967 |
| 1242 | Eswatini | SWZ | 2010 | 4035.534481 |
| 1243 | Ethiopia | ETH | 2020 | 918.652594 |
| 1244 | Ethiopia | ETH | 2019 | 840.449601 |
| 1245 | Ethiopia | ETH | 2018 | 758.297694 |
| 1246 | Ethiopia | ETH | 2017 | 755.752644 |
| 1247 | Ethiopia | ETH | 2016 | 705.617509 |
| 1248 | Ethiopia | ETH | 2015 | 630.312619 |
| 1249 | Ethiopia | ETH | 2014 | 557.534148 |
| 1250 | Ethiopia | ETH | 2013 | 490.792478 |
| 1251 | Ethiopia | ETH | 2012 | 458.550921 |
| 1252 | Ethiopia | ETH | 2011 | 348.001348 |
| 1253 | Ethiopia | ETH | 2010 | 335.438495 |
| 1254 | Faroe Islands | FRO | 2020 | 62234.968680 |
| 1255 | Faroe Islands | FRO | 2019 | 63203.744785 |
| 1256 | Faroe Islands | FRO | 2018 | 62576.801638 |
| 1257 | Faroe Islands | FRO | 2017 | 59328.237664 |
| 1258 | Faroe Islands | FRO | 2016 | 56833.916541 |
| 1259 | Faroe Islands | FRO | 2015 | 52726.687378 |
| 1260 | Faroe Islands | FRO | 2014 | 60126.125643 |
| 1261 | Faroe Islands | FRO | 2013 | 55560.133027 |
| 1262 | Faroe Islands | FRO | 2012 | 50157.058789 |
| 1263 | Faroe Islands | FRO | 2011 | 51786.480992 |
| 1264 | Faroe Islands | FRO | 2010 | 48167.667514 |
| 1265 | Fiji | FJI | 2020 | 4815.689148 |
| 1266 | Fiji | FJI | 2019 | 5927.724208 |
| 1267 | Fiji | FJI | 2018 | 6073.394579 |
| 1268 | Fiji | FJI | 2017 | 5825.199665 |
| 1269 | Fiji | FJI | 2016 | 5368.433492 |
| 1270 | Fiji | FJI | 2015 | 5105.189612 |
| 1271 | Fiji | FJI | 2014 | 5305.064432 |
| 1272 | Fiji | FJI | 2013 | 4586.955211 |
| 1273 | Fiji | FJI | 2012 | 4359.792400 |
| 1274 | Fiji | FJI | 2011 | 4160.721193 |
| 1275 | Fiji | FJI | 2010 | 3469.149643 |
| 1276 | Finland | FIN | 2020 | 49169.719339 |
| 1277 | Finland | FIN | 2019 | 48629.858228 |
| 1278 | Finland | FIN | 2018 | 49987.626158 |
| 1279 | Finland | FIN | 2017 | 46412.136478 |
| 1280 | Finland | FIN | 2016 | 43814.026506 |
| 1281 | Finland | FIN | 2015 | 42801.908117 |
| 1282 | Finland | FIN | 2014 | 50327.240290 |
| 1283 | Finland | FIN | 2013 | 49892.223363 |
| 1284 | Finland | FIN | 2012 | 47708.061278 |
| 1285 | Finland | FIN | 2011 | 51148.931637 |
| 1286 | Finland | FIN | 2010 | 46505.303179 |
| 1287 | France | FRA | 2020 | 39179.744260 |
| 1288 | France | FRA | 2019 | 40494.898294 |
| 1289 | France | FRA | 2018 | 41557.854859 |
| 1290 | France | FRA | 2017 | 38781.049487 |
| 1291 | France | FRA | 2016 | 37062.533572 |
| 1292 | France | FRA | 2015 | 36652.922305 |
| 1293 | France | FRA | 2014 | 43068.548724 |
| 1294 | France | FRA | 2013 | 42602.717965 |
| 1295 | France | FRA | 2012 | 40870.852365 |
| 1296 | France | FRA | 2011 | 43846.466076 |
| 1297 | France | FRA | 2010 | 40676.064791 |
| 1298 | French Polynesia | PYF | 2020 | 19185.697770 |
| 1299 | French Polynesia | PYF | 2019 | 20093.208581 |
| 1300 | French Polynesia | PYF | 2018 | 20614.894368 |
| 1301 | French Polynesia | PYF | 2017 | 19743.959021 |
| 1302 | French Polynesia | PYF | 2016 | 18726.639470 |
| 1303 | French Polynesia | PYF | 2015 | 18252.514203 |
| 1304 | French Polynesia | PYF | 2014 | 21223.075488 |
| 1305 | French Polynesia | PYF | 2013 | 20941.517340 |
| 1306 | French Polynesia | PYF | 2012 | 19864.535700 |
| 1307 | French Polynesia | PYF | 2011 | 21747.988842 |
| 1308 | French Polynesia | PYF | 2010 | 21447.858255 |
| 1309 | Gabon | GAB | 2020 | 6680.082665 |
| 1310 | Gabon | GAB | 2019 | 7523.862281 |
| 1311 | Gabon | GAB | 2018 | 7694.906051 |
| 1312 | Gabon | GAB | 2017 | 6975.695192 |
| 1313 | Gabon | GAB | 2016 | 6722.198223 |
| 1314 | Gabon | GAB | 2015 | 7090.454634 |
| 1315 | Gabon | GAB | 2014 | 9255.368035 |
| 1316 | Gabon | GAB | 2013 | 9250.081115 |
| 1317 | Gabon | GAB | 2012 | 9348.514876 |
| 1318 | Gabon | GAB | 2011 | 10273.798445 |
| 1319 | Gabon | GAB | 2010 | 8399.597348 |
| 1320 | Gambia, The | GMB | 2020 | 704.030463 |
| 1321 | Gambia, The | GMB | 2019 | 722.875356 |
| 1322 | Gambia, The | GMB | 2018 | 683.324633 |
| 1323 | Gambia, The | GMB | 2017 | 632.001024 |
| 1324 | Gambia, The | GMB | 2016 | 640.676265 |
| 1325 | Gambia, The | GMB | 2015 | 611.671219 |
| 1326 | Gambia, The | GMB | 2014 | 561.649635 |
| 1327 | Gambia, The | GMB | 2013 | 647.385535 |
| 1328 | Gambia, The | GMB | 2012 | 686.557558 |
| 1329 | Gambia, The | GMB | 2011 | 705.477495 |
| 1330 | Gambia, The | GMB | 2010 | 796.631829 |
| 1331 | Georgia | GEO | 2020 | 4255.742993 |
| 1332 | Georgia | GEO | 2019 | 4696.150586 |
| 1333 | Georgia | GEO | 2018 | 4722.042423 |
| 1334 | Georgia | GEO | 2017 | 4356.928016 |
| 1335 | Georgia | GEO | 2016 | 4062.126978 |
| 1336 | Georgia | GEO | 2015 | 4014.111651 |
| 1337 | Georgia | GEO | 2014 | 4739.276913 |
| 1338 | Georgia | GEO | 2013 | 4623.884714 |
| 1339 | Georgia | GEO | 2012 | 4421.930712 |
| 1340 | Georgia | GEO | 2011 | 4021.755230 |
| 1341 | Georgia | GEO | 2010 | 3233.219752 |
| 1342 | Germany | DEU | 2020 | 46749.476228 |
| 1343 | Germany | DEU | 2019 | 46805.138433 |
| 1344 | Germany | DEU | 2018 | 47939.278288 |
| 1345 | Germany | DEU | 2017 | 44652.589172 |
| 1346 | Germany | DEU | 2016 | 42136.120791 |
| 1347 | Germany | DEU | 2015 | 41103.256436 |
| 1348 | Germany | DEU | 2014 | 48023.869985 |
| 1349 | Germany | DEU | 2013 | 46298.922918 |
| 1350 | Germany | DEU | 2012 | 43855.854466 |
| 1351 | Germany | DEU | 2011 | 46705.895796 |
| 1352 | Germany | DEU | 2010 | 41572.455948 |
| 1353 | Ghana | GHA | 2020 | 2176.576218 |
| 1354 | Ghana | GHA | 2019 | 2167.925440 |
| 1355 | Ghana | GHA | 2018 | 2180.029684 |
| 1356 | Ghana | GHA | 2017 | 1998.722666 |
| 1357 | Ghana | GHA | 2016 | 1900.397674 |
| 1358 | Ghana | GHA | 2015 | 1711.271317 |
| 1359 | Ghana | GHA | 2014 | 1942.921869 |
| 1360 | Ghana | GHA | 2013 | 2282.407501 |
| 1361 | Ghana | GHA | 2012 | 1536.619635 |
| 1362 | Ghana | GHA | 2011 | 1501.059171 |
| 1363 | Ghana | GHA | 2010 | 1258.964197 |
| 1364 | Gibraltar | GIB | 2020 | NaN |
| 1365 | Gibraltar | GIB | 2019 | NaN |
| 1366 | Gibraltar | GIB | 2018 | NaN |
| 1367 | Gibraltar | GIB | 2017 | NaN |
| 1368 | Gibraltar | GIB | 2016 | NaN |
| 1369 | Gibraltar | GIB | 2015 | NaN |
| 1370 | Gibraltar | GIB | 2014 | NaN |
| 1371 | Gibraltar | GIB | 2013 | NaN |
| 1372 | Gibraltar | GIB | 2012 | NaN |
| 1373 | Gibraltar | GIB | 2011 | NaN |
| 1374 | Gibraltar | GIB | 2010 | NaN |
| 1375 | Greece | GRC | 2020 | 17617.291506 |
| 1376 | Greece | GRC | 2019 | 19143.887617 |
| 1377 | Greece | GRC | 2018 | 19756.990456 |
| 1378 | Greece | GRC | 2017 | 18582.089341 |
| 1379 | Greece | GRC | 2016 | 17923.966813 |
| 1380 | Greece | GRC | 2015 | 18083.877906 |
| 1381 | Greece | GRC | 2014 | 21616.710009 |
| 1382 | Greece | GRC | 2013 | 21787.787764 |
| 1383 | Greece | GRC | 2012 | 21912.998288 |
| 1384 | Greece | GRC | 2011 | 25483.882564 |
| 1385 | Greece | GRC | 2010 | 26716.648826 |
| 1386 | Greenland | GRL | 2020 | 54693.076680 |
| 1387 | Greenland | GRL | 2019 | 53309.203591 |
| 1388 | Greenland | GRL | 2018 | 54545.135858 |
| 1389 | Greenland | GRL | 2017 | 50765.749467 |
| 1390 | Greenland | GRL | 2016 | 48181.745354 |
| 1391 | Greenland | GRL | 2015 | 44536.354971 |
| 1392 | Greenland | GRL | 2014 | 50485.224414 |
| 1393 | Greenland | GRL | 2013 | 47535.488379 |
| 1394 | Greenland | GRL | 2012 | 45936.956282 |
| 1395 | Greenland | GRL | 2011 | 47186.875997 |
| 1396 | Greenland | GRL | 2010 | 43988.528029 |
| 1397 | Grenada | GRD | 2020 | 8437.536782 |
| 1398 | Grenada | GRD | 2019 | 9887.920742 |
| 1399 | Grenada | GRD | 2018 | 9574.310271 |
| 1400 | Grenada | GRD | 2017 | 9309.261296 |
| 1401 | Grenada | GRD | 2016 | 8849.513535 |
| 1402 | Grenada | GRD | 2015 | 8379.621847 |
| 1403 | Grenada | GRD | 2014 | 7726.378262 |
| 1404 | Grenada | GRD | 2013 | 7205.254765 |
| 1405 | Grenada | GRD | 2012 | 6900.765076 |
| 1406 | Grenada | GRD | 2011 | 6775.749278 |
| 1407 | Grenada | GRD | 2010 | 6760.974884 |
| 1408 | Guam | GUM | 2020 | 34780.861662 |
| 1409 | Guam | GUM | 2019 | 37752.633077 |
| 1410 | Guam | GUM | 2018 | 35902.725904 |
| 1411 | Guam | GUM | 2017 | 35663.025041 |
| 1412 | Guam | GUM | 2016 | 35052.807908 |
| 1413 | Guam | GUM | 2015 | 34522.377930 |
| 1414 | Guam | GUM | 2014 | 33483.941436 |
| 1415 | Guam | GUM | 2013 | 32318.890898 |
| 1416 | Guam | GUM | 2012 | 31642.146257 |
| 1417 | Guam | GUM | 2011 | 30087.715591 |
| 1418 | Guam | GUM | 2010 | 30011.218580 |
| 1419 | Guatemala | GTM | 2020 | 4609.897258 |
| 1420 | Guatemala | GTM | 2019 | 4647.807541 |
| 1421 | Guatemala | GTM | 2018 | 4485.752135 |
| 1422 | Guatemala | GTM | 2017 | 4454.024509 |
| 1423 | Guatemala | GTM | 2016 | 4173.281349 |
| 1424 | Guatemala | GTM | 2015 | 3994.629085 |
| 1425 | Guatemala | GTM | 2014 | 3779.626205 |
| 1426 | Guatemala | GTM | 2013 | 3522.767429 |
| 1427 | Guatemala | GTM | 2012 | 3355.034777 |
| 1428 | Guatemala | GTM | 2011 | 3228.038278 |
| 1429 | Guatemala | GTM | 2010 | 2852.557593 |
| 1430 | Guinea | GIN | 2020 | 1073.659339 |
| 1431 | Guinea | GIN | 2019 | 1043.899886 |
| 1432 | Guinea | GIN | 2018 | 944.417269 |
| 1433 | Guinea | GIN | 2017 | 843.464279 |
| 1434 | Guinea | GIN | 2016 | 720.473255 |
| 1435 | Guinea | GIN | 2015 | 756.425590 |
| 1436 | Guinea | GIN | 2014 | 774.569040 |
| 1437 | Guinea | GIN | 2013 | 757.692273 |
| 1438 | Guinea | GIN | 2012 | 707.967678 |
| 1439 | Guinea | GIN | 2011 | 644.502549 |
| 1440 | Guinea | GIN | 2010 | 667.281602 |
| 1441 | Guinea-Bissau | GNB | 2020 | 710.258133 |
| 1442 | Guinea-Bissau | GNB | 2019 | 730.611432 |
| 1443 | Guinea-Bissau | GNB | 2018 | 781.644368 |
| 1444 | Guinea-Bissau | GNB | 2017 | 718.245738 |
| 1445 | Guinea-Bissau | GNB | 2016 | 642.666390 |
| 1446 | Guinea-Bissau | GNB | 2015 | 585.957013 |
| 1447 | Guinea-Bissau | GNB | 2014 | 605.122546 |
| 1448 | Guinea-Bissau | GNB | 2013 | 616.159929 |
| 1449 | Guinea-Bissau | GNB | 2012 | 598.572626 |
| 1450 | Guinea-Bissau | GNB | 2011 | 683.534476 |
| 1451 | Guinea-Bissau | GNB | 2010 | 542.284101 |
| 1452 | Guyana | GUY | 2020 | 6863.074346 |
| 1453 | Guyana | GUY | 2019 | 6477.296726 |
| 1454 | Guyana | GUY | 2018 | 6094.909837 |
| 1455 | Guyana | GUY | 2017 | 6220.978568 |
| 1456 | Guyana | GUY | 2016 | 5905.380196 |
| 1457 | Guyana | GUY | 2015 | 5668.429765 |
| 1458 | Guyana | GUY | 2014 | 5495.377084 |
| 1459 | Guyana | GUY | 2013 | 5576.250215 |
| 1460 | Guyana | GUY | 2012 | 5461.390085 |
| 1461 | Guyana | GUY | 2011 | 4960.004726 |
| 1462 | Guyana | GUY | 2010 | 4589.872498 |
| 1463 | Haiti | HTI | 2020 | 1283.141228 |
| 1464 | Haiti | HTI | 2019 | 1345.475055 |
| 1465 | Haiti | HTI | 2018 | 1489.578406 |
| 1466 | Haiti | HTI | 2017 | 1389.358623 |
| 1467 | Haiti | HTI | 2016 | 1313.186095 |
| 1468 | Haiti | HTI | 2015 | 1405.714786 |
| 1469 | Haiti | HTI | 2014 | 1454.649175 |
| 1470 | Haiti | HTI | 2013 | 1452.313548 |
| 1471 | Haiti | HTI | 2012 | 1356.172777 |
| 1472 | Haiti | HTI | 2011 | 1306.845319 |
| 1473 | Haiti | HTI | 2010 | 1204.862055 |
| 1474 | Honduras | HND | 2020 | 2354.121434 |
| 1475 | Honduras | HND | 2019 | 2519.366185 |
| 1476 | Honduras | HND | 2018 | 2457.686042 |
| 1477 | Honduras | HND | 2017 | 2403.306088 |
| 1478 | Honduras | HND | 2016 | 2295.536270 |
| 1479 | Honduras | HND | 2015 | 2257.225284 |
| 1480 | Honduras | HND | 2014 | 2164.424550 |
| 1481 | Honduras | HND | 2013 | 2064.550536 |
| 1482 | Honduras | HND | 2012 | 2107.345428 |
| 1483 | Honduras | HND | 2011 | 2053.959695 |
| 1484 | Honduras | HND | 2010 | 1874.271704 |
| 1485 | Hong Kong SAR, China | HKG | 2020 | 46109.229995 |
| 1486 | Hong Kong SAR, China | HKG | 2019 | 48359.001195 |
| 1487 | Hong Kong SAR, China | HKG | 2018 | 48537.566889 |
| 1488 | Hong Kong SAR, China | HKG | 2017 | 46160.429791 |
| 1489 | Hong Kong SAR, China | HKG | 2016 | 43734.198070 |
| 1490 | Hong Kong SAR, China | HKG | 2015 | 42432.161974 |
| 1491 | Hong Kong SAR, China | HKG | 2014 | 40315.373951 |
| 1492 | Hong Kong SAR, China | HKG | 2013 | 38403.777715 |
| 1493 | Hong Kong SAR, China | HKG | 2012 | 36730.796196 |
| 1494 | Hong Kong SAR, China | HKG | 2011 | 35142.487934 |
| 1495 | Hong Kong SAR, China | HKG | 2010 | 32550.136489 |
| 1496 | Hungary | HUN | 2020 | 16125.609409 |
| 1497 | Hungary | HUN | 2019 | 16786.213640 |
| 1498 | Hungary | HUN | 2018 | 16425.205030 |
| 1499 | Hungary | HUN | 2017 | 14621.239596 |
| 1500 | Hungary | HUN | 2016 | 13104.699546 |
| 1501 | Hungary | HUN | 2015 | 12717.038597 |
| 1502 | Hungary | HUN | 2014 | 14294.258418 |
| 1503 | Hungary | HUN | 2013 | 13715.070359 |
| 1504 | Hungary | HUN | 2012 | 12984.836573 |
| 1505 | Hungary | HUN | 2011 | 14234.471577 |
| 1506 | Hungary | HUN | 2010 | 13217.504595 |
| 1507 | Iceland | ISL | 2020 | 58848.418124 |
| 1508 | Iceland | ISL | 2019 | 68452.236223 |
| 1509 | Iceland | ISL | 2018 | 74452.189073 |
| 1510 | Iceland | ISL | 2017 | 72010.149032 |
| 1511 | Iceland | ISL | 2016 | 61987.926362 |
| 1512 | Iceland | ISL | 2015 | 52951.681511 |
| 1513 | Iceland | ISL | 2014 | 54576.744815 |
| 1514 | Iceland | ISL | 2013 | 49804.982998 |
| 1515 | Iceland | ISL | 2012 | 45995.547879 |
| 1516 | Iceland | ISL | 2011 | 47714.592231 |
| 1517 | Iceland | ISL | 2010 | 43237.072949 |
| 1518 | India | IND | 2020 | 1913.219733 |
| 1519 | India | IND | 2019 | 2050.163800 |
| 1520 | India | IND | 2018 | 1974.377731 |
| 1521 | India | IND | 2017 | 1957.969813 |
| 1522 | India | IND | 2016 | 1714.279537 |
| 1523 | India | IND | 2015 | 1590.174331 |
| 1524 | India | IND | 2014 | 1559.863779 |
| 1525 | India | IND | 2013 | 1438.057005 |
| 1526 | India | IND | 2012 | 1434.017987 |
| 1527 | India | IND | 2011 | 1449.603301 |
| 1528 | India | IND | 2010 | 1350.634470 |
| 1529 | Indonesia | IDN | 2020 | 3895.618152 |
| 1530 | Indonesia | IDN | 2019 | 4151.227554 |
| 1531 | Indonesia | IDN | 2018 | 3902.661676 |
| 1532 | Indonesia | IDN | 2017 | 3839.785075 |
| 1533 | Indonesia | IDN | 2016 | 3558.818852 |
| 1534 | Indonesia | IDN | 2015 | 3322.581679 |
| 1535 | Indonesia | IDN | 2014 | 3476.624854 |
| 1536 | Indonesia | IDN | 2013 | 3602.885517 |
| 1537 | Indonesia | IDN | 2012 | 3668.212083 |
| 1538 | Indonesia | IDN | 2011 | 3613.800888 |
| 1539 | Indonesia | IDN | 2010 | 3094.443079 |
| 1540 | Iran, Islamic Rep. | IRN | 2020 | 2746.419483 |
| 1541 | Iran, Islamic Rep. | IRN | 2019 | 3276.753265 |
| 1542 | Iran, Islamic Rep. | IRN | 2018 | 3850.751253 |
| 1543 | Iran, Islamic Rep. | IRN | 2017 | 5758.590728 |
| 1544 | Iran, Islamic Rep. | IRN | 2016 | 5497.243233 |
| 1545 | Iran, Islamic Rep. | IRN | 2015 | 4990.936795 |
| 1546 | Iran, Islamic Rep. | IRN | 2014 | 5757.543333 |
| 1547 | Iran, Islamic Rep. | IRN | 2013 | 6280.681867 |
| 1548 | Iran, Islamic Rep. | IRN | 2012 | 8329.002067 |
| 1549 | Iran, Islamic Rep. | IRN | 2011 | 8201.581678 |
| 1550 | Iran, Islamic Rep. | IRN | 2010 | 6458.573956 |
| 1551 | Iraq | IRQ | 2020 | 4251.337253 |
| 1552 | Iraq | IRQ | 2019 | 5621.181695 |
| 1553 | Iraq | IRQ | 2018 | 5601.467061 |
| 1554 | Iraq | IRQ | 2017 | 4725.193573 |
| 1555 | Iraq | IRQ | 2016 | 4305.202702 |
| 1556 | Iraq | IRQ | 2015 | 4416.942924 |
| 1557 | Iraq | IRQ | 2014 | 6215.986033 |
| 1558 | Iraq | IRQ | 2013 | 6612.902252 |
| 1559 | Iraq | IRQ | 2012 | 6437.503076 |
| 1560 | Iraq | IRQ | 2011 | 5736.898959 |
| 1561 | Iraq | IRQ | 2010 | 4430.426242 |
| 1562 | Ireland | IRL | 2020 | 85973.088488 |
| 1563 | Ireland | IRL | 2019 | 80848.301902 |
| 1564 | Ireland | IRL | 2018 | 79446.939109 |
| 1565 | Ireland | IRL | 2017 | 70150.737016 |
| 1566 | Ireland | IRL | 2016 | 62784.065688 |
| 1567 | Ireland | IRL | 2015 | 62179.264266 |
| 1568 | Ireland | IRL | 2014 | 55752.764984 |
| 1569 | Ireland | IRL | 2013 | 51496.961685 |
| 1570 | Ireland | IRL | 2012 | 48943.820646 |
| 1571 | Ireland | IRL | 2011 | 52219.705733 |
| 1572 | Ireland | IRL | 2010 | 48663.600444 |
| 1573 | Isle of Man | IMN | 2020 | 79530.605484 |
| 1574 | Isle of Man | IMN | 2019 | 87152.453018 |
| 1575 | Isle of Man | IMN | 2018 | 89425.891389 |
| 1576 | Isle of Man | IMN | 2017 | 83510.303746 |
| 1577 | Isle of Man | IMN | 2016 | 82041.621050 |
| 1578 | Isle of Man | IMN | 2015 | 84753.456728 |
| 1579 | Isle of Man | IMN | 2014 | 91881.128361 |
| 1580 | Isle of Man | IMN | 2013 | 83204.747170 |
| 1581 | Isle of Man | IMN | 2012 | 79326.382999 |
| 1582 | Isle of Man | IMN | 2011 | 77838.396926 |
| 1583 | Isle of Man | IMN | 2010 | 70625.168540 |
| 1584 | Israel | ISR | 2020 | 44846.791595 |
| 1585 | Israel | ISR | 2019 | 44452.232562 |
| 1586 | Israel | ISR | 2018 | 42406.845426 |
| 1587 | Israel | ISR | 2017 | 41114.781708 |
| 1588 | Israel | ISR | 2016 | 37690.473951 |
| 1589 | Israel | ISR | 2015 | 36206.522217 |
| 1590 | Israel | ISR | 2014 | 38259.681096 |
| 1591 | Israel | ISR | 2013 | 36941.842357 |
| 1592 | Israel | ISR | 2012 | 33156.228316 |
| 1593 | Israel | ISR | 2011 | 34354.716118 |
| 1594 | Israel | ISR | 2010 | 31266.605317 |
| 1595 | Italy | ITA | 2020 | 31922.919163 |
| 1596 | Italy | ITA | 2019 | 33673.750963 |
| 1597 | Italy | ITA | 2018 | 34622.169666 |
| 1598 | Italy | ITA | 2017 | 32406.720315 |
| 1599 | Italy | ITA | 2016 | 30960.731509 |
| 1600 | Italy | ITA | 2015 | 30242.386135 |
| 1601 | Italy | ITA | 2014 | 35565.721377 |
| 1602 | Italy | ITA | 2013 | 35560.081406 |
| 1603 | Italy | ITA | 2012 | 35051.521270 |
| 1604 | Italy | ITA | 2011 | 38649.639484 |
| 1605 | Italy | ITA | 2010 | 36035.644995 |
| 1606 | Jamaica | JAM | 2020 | 4897.264750 |
| 1607 | Jamaica | JAM | 2019 | 5626.170473 |
| 1608 | Jamaica | JAM | 2018 | 5594.493573 |
| 1609 | Jamaica | JAM | 2017 | 5273.149027 |
| 1610 | Jamaica | JAM | 2016 | 5022.700192 |
| 1611 | Jamaica | JAM | 2015 | 5077.550984 |
| 1612 | Jamaica | JAM | 2014 | 4991.561532 |
| 1613 | Jamaica | JAM | 2013 | 5143.722183 |
| 1614 | Jamaica | JAM | 2012 | 5365.242172 |
| 1615 | Jamaica | JAM | 2011 | 5259.931753 |
| 1616 | Jamaica | JAM | 2010 | 4835.791087 |
| 1617 | Japan | JPN | 2020 | 40040.765506 |
| 1618 | Japan | JPN | 2019 | 40415.956765 |
| 1619 | Japan | JPN | 2018 | 39751.133098 |
| 1620 | Japan | JPN | 2017 | 38834.052934 |
| 1621 | Japan | JPN | 2016 | 39375.473162 |
| 1622 | Japan | JPN | 2015 | 34960.639384 |
| 1623 | Japan | JPN | 2014 | 38475.395246 |
| 1624 | Japan | JPN | 2013 | 40898.647896 |
| 1625 | Japan | JPN | 2012 | 49145.280431 |
| 1626 | Japan | JPN | 2011 | 48760.078949 |
| 1627 | Japan | JPN | 2010 | 44968.156235 |
| 1628 | Jordan | JOR | 2020 | 3998.673138 |
| 1629 | Jordan | JOR | 2019 | 4159.653754 |
| 1630 | Jordan | JOR | 2018 | 4146.407311 |
| 1631 | Jordan | JOR | 2017 | 4073.116403 |
| 1632 | Jordan | JOR | 2016 | 4003.404746 |
| 1633 | Jordan | JOR | 2015 | 4064.253010 |
| 1634 | Jordan | JOR | 2014 | 4255.894302 |
| 1635 | Jordan | JOR | 2013 | 4477.618321 |
| 1636 | Jordan | JOR | 2012 | 4386.461819 |
| 1637 | Jordan | JOR | 2011 | 4152.493981 |
| 1638 | Jordan | JOR | 2010 | 3914.701231 |
| 1639 | Kazakhstan | KAZ | 2020 | 9121.636409 |
| 1640 | Kazakhstan | KAZ | 2019 | 9812.595526 |
| 1641 | Kazakhstan | KAZ | 2018 | 9812.625431 |
| 1642 | Kazakhstan | KAZ | 2017 | 9247.580679 |
| 1643 | Kazakhstan | KAZ | 2016 | 7714.841844 |
| 1644 | Kazakhstan | KAZ | 2015 | 10510.770324 |
| 1645 | Kazakhstan | KAZ | 2014 | 12807.263045 |
| 1646 | Kazakhstan | KAZ | 2013 | 13890.633969 |
| 1647 | Kazakhstan | KAZ | 2012 | 12386.699265 |
| 1648 | Kazakhstan | KAZ | 2011 | 11633.998584 |
| 1649 | Kazakhstan | KAZ | 2010 | 9070.488253 |
| 1650 | Kenya | KEN | 2020 | 1936.250755 |
| 1651 | Kenya | KEN | 2019 | 1970.080070 |
| 1652 | Kenya | KEN | 2018 | 1845.783414 |
| 1653 | Kenya | KEN | 2017 | 1675.988422 |
| 1654 | Kenya | KEN | 2016 | 1562.076619 |
| 1655 | Kenya | KEN | 2015 | 1496.653573 |
| 1656 | Kenya | KEN | 2014 | 1489.919721 |
| 1657 | Kenya | KEN | 2013 | 1376.829205 |
| 1658 | Kenya | KEN | 2012 | 1289.780791 |
| 1659 | Kenya | KEN | 2011 | 1099.315465 |
| 1660 | Kenya | KEN | 2010 | 1093.639624 |
| 1661 | Kiribati | KIR | 2020 | 1403.993853 |
| 1662 | Kiribati | KIR | 2019 | 1410.014643 |
| 1663 | Kiribati | KIR | 2018 | 1607.229825 |
| 1664 | Kiribati | KIR | 2017 | 1566.447136 |
| 1665 | Kiribati | KIR | 2016 | 1506.231003 |
| 1666 | Kiribati | KIR | 2015 | 1459.143983 |
| 1667 | Kiribati | KIR | 2014 | 1546.881768 |
| 1668 | Kiribati | KIR | 2013 | 1628.642594 |
| 1669 | Kiribati | KIR | 2012 | 1698.919124 |
| 1670 | Kiribati | KIR | 2011 | 1644.407553 |
| 1671 | Kiribati | KIR | 2010 | 1438.081413 |
| 1672 | Korea, Dem. People's Rep. | PRK | 2020 | NaN |
| 1673 | Korea, Dem. People's Rep. | PRK | 2019 | NaN |
| 1674 | Korea, Dem. People's Rep. | PRK | 2018 | NaN |
| 1675 | Korea, Dem. People's Rep. | PRK | 2017 | NaN |
| 1676 | Korea, Dem. People's Rep. | PRK | 2016 | NaN |
| 1677 | Korea, Dem. People's Rep. | PRK | 2015 | NaN |
| 1678 | Korea, Dem. People's Rep. | PRK | 2014 | NaN |
| 1679 | Korea, Dem. People's Rep. | PRK | 2013 | NaN |
| 1680 | Korea, Dem. People's Rep. | PRK | 2012 | NaN |
| 1681 | Korea, Dem. People's Rep. | PRK | 2011 | NaN |
| 1682 | Korea, Dem. People's Rep. | PRK | 2010 | NaN |
| 1683 | Korea, Rep. | KOR | 2020 | 31721.298914 |
| 1684 | Korea, Rep. | KOR | 2019 | 31902.416905 |
| 1685 | Korea, Rep. | KOR | 2018 | 33447.156284 |
| 1686 | Korea, Rep. | KOR | 2017 | 31600.735874 |
| 1687 | Korea, Rep. | KOR | 2016 | 29280.440317 |
| 1688 | Korea, Rep. | KOR | 2015 | 28737.439171 |
| 1689 | Korea, Rep. | KOR | 2014 | 29252.931238 |
| 1690 | Korea, Rep. | KOR | 2013 | 27179.517015 |
| 1691 | Korea, Rep. | KOR | 2012 | 25459.168900 |
| 1692 | Korea, Rep. | KOR | 2011 | 25097.595427 |
| 1693 | Korea, Rep. | KOR | 2010 | 23079.260126 |
| 1694 | Kosovo | XKX | 2020 | 4310.934002 |
| 1695 | Kosovo | XKX | 2019 | 4416.029253 |
| 1696 | Kosovo | XKX | 2018 | 4384.188680 |
| 1697 | Kosovo | XKX | 2017 | 4009.353811 |
| 1698 | Kosovo | XKX | 2016 | 3759.472855 |
| 1699 | Kosovo | XKX | 2015 | 3520.782075 |
| 1700 | Kosovo | XKX | 2014 | 3902.530841 |
| 1701 | Kosovo | XKX | 2013 | 3704.562803 |
| 1702 | Kosovo | XKX | 2012 | 3410.693255 |
| 1703 | Kosovo | XKX | 2011 | 3540.822786 |
| 1704 | Kosovo | XKX | 2010 | 3009.523425 |
| 1705 | Kuwait | KWT | 2020 | 24297.710802 |
| 1706 | Kuwait | KWT | 2019 | 30666.237131 |
| 1707 | Kuwait | KWT | 2018 | 32012.187525 |
| 1708 | Kuwait | KWT | 2017 | 29258.266327 |
| 1709 | Kuwait | KWT | 2016 | 27026.687660 |
| 1710 | Kuwait | KWT | 2015 | 29315.198508 |
| 1711 | Kuwait | KWT | 2014 | 43239.835178 |
| 1712 | Kuwait | KWT | 2013 | 47762.796703 |
| 1713 | Kuwait | KWT | 2012 | 51271.067757 |
| 1714 | Kuwait | KWT | 2011 | 49010.310500 |
| 1715 | Kuwait | KWT | 2010 | 39212.579414 |
| 1716 | Kyrgyz Republic | KGZ | 2020 | 1256.929226 |
| 1717 | Kyrgyz Republic | KGZ | 2019 | 1451.515638 |
| 1718 | Kyrgyz Republic | KGZ | 2018 | 1308.139785 |
| 1719 | Kyrgyz Republic | KGZ | 2017 | 1242.770220 |
| 1720 | Kyrgyz Republic | KGZ | 2016 | 1120.667058 |
| 1721 | Kyrgyz Republic | KGZ | 2015 | 1121.082696 |
| 1722 | Kyrgyz Republic | KGZ | 2014 | 1279.770784 |
| 1723 | Kyrgyz Republic | KGZ | 2013 | 1282.438248 |
| 1724 | Kyrgyz Republic | KGZ | 2012 | 1177.975261 |
| 1725 | Kyrgyz Republic | KGZ | 2011 | 1123.883144 |
| 1726 | Kyrgyz Republic | KGZ | 2010 | 880.038522 |
| 1727 | Lao PDR | LAO | 2020 | 2593.355097 |
| 1728 | Lao PDR | LAO | 2019 | 2598.505523 |
| 1729 | Lao PDR | LAO | 2018 | 2553.361866 |
| 1730 | Lao PDR | LAO | 2017 | 2439.463355 |
| 1731 | Lao PDR | LAO | 2016 | 2309.049076 |
| 1732 | Lao PDR | LAO | 2015 | 2125.459057 |
| 1733 | Lao PDR | LAO | 2014 | 1984.508670 |
| 1734 | Lao PDR | LAO | 2013 | 1815.440238 |
| 1735 | Lao PDR | LAO | 2012 | 1566.009745 |
| 1736 | Lao PDR | LAO | 2011 | 1363.725290 |
| 1737 | Lao PDR | LAO | 2010 | 1127.835236 |
| 1738 | Latvia | LVA | 2020 | 18096.202707 |
| 1739 | Latvia | LVA | 2019 | 17883.349411 |
| 1740 | Latvia | LVA | 2018 | 17865.031095 |
| 1741 | Latvia | LVA | 2017 | 15695.115154 |
| 1742 | Latvia | LVA | 2016 | 14331.751589 |
| 1743 | Latvia | LVA | 2015 | 13786.456795 |
| 1744 | Latvia | LVA | 2014 | 15742.391338 |
| 1745 | Latvia | LVA | 2013 | 15007.491856 |
| 1746 | Latvia | LVA | 2012 | 13847.337939 |
| 1747 | Latvia | LVA | 2011 | 13338.962235 |
| 1748 | Latvia | LVA | 2010 | 11420.994003 |
| 1749 | Lebanon | LBN | 2020 | 5599.957523 |
| 1750 | Lebanon | LBN | 2019 | 8925.421860 |
| 1751 | Lebanon | LBN | 2018 | 9225.845155 |
| 1752 | Lebanon | LBN | 2017 | 8679.897422 |
| 1753 | Lebanon | LBN | 2016 | 8172.299476 |
| 1754 | Lebanon | LBN | 2015 | 7802.751368 |
| 1755 | Lebanon | LBN | 2014 | 7665.379692 |
| 1756 | Lebanon | LBN | 2013 | 8255.209211 |
| 1757 | Lebanon | LBN | 2012 | 8500.180563 |
| 1758 | Lebanon | LBN | 2011 | 7914.109568 |
| 1759 | Lebanon | LBN | 2010 | 7695.245415 |
| 1760 | Lesotho | LSO | 2020 | 917.356381 |
| 1761 | Lesotho | LSO | 2019 | 1061.223356 |
| 1762 | Lesotho | LSO | 2018 | 1162.978854 |
| 1763 | Lesotho | LSO | 2017 | 1062.456192 |
| 1764 | Lesotho | LSO | 2016 | 994.239764 |
| 1765 | Lesotho | LSO | 2015 | 1113.836835 |
| 1766 | Lesotho | LSO | 2014 | 1165.050650 |
| 1767 | Lesotho | LSO | 2013 | 1141.360923 |
| 1768 | Lesotho | LSO | 2012 | 1205.859985 |
| 1769 | Lesotho | LSO | 2011 | 1265.857945 |
| 1770 | Lesotho | LSO | 2010 | 1104.811547 |
| 1771 | Liberia | LBR | 2020 | 597.529692 |
| 1772 | Liberia | LBR | 2019 | 665.878448 |
| 1773 | Liberia | LBR | 2018 | 700.037039 |
| 1774 | Liberia | LBR | 2017 | 706.892692 |
| 1775 | Liberia | LBR | 2016 | 722.131227 |
| 1776 | Liberia | LBR | 2015 | 699.662947 |
| 1777 | Liberia | LBR | 2014 | 713.734882 |
| 1778 | Liberia | LBR | 2013 | 717.635753 |
| 1779 | Liberia | LBR | 2012 | 644.455577 |
| 1780 | Liberia | LBR | 2011 | 573.526422 |
| 1781 | Liberia | LBR | 2010 | 497.020365 |
| 1782 | Libya | LBY | 2020 | 7034.658364 |
| 1783 | Libya | LBY | 2019 | 10542.429020 |
| 1784 | Libya | LBY | 2018 | 11838.298707 |
| 1785 | Libya | LBY | 2017 | 10529.116269 |
| 1786 | Libya | LBY | 2016 | 7945.006050 |
| 1787 | Libya | LBY | 2015 | 7867.515731 |
| 1788 | Libya | LBY | 2014 | 9408.752546 |
| 1789 | Libya | LBY | 2013 | 12589.529715 |
| 1790 | Libya | LBY | 2012 | 15765.419791 |
| 1791 | Libya | LBY | 2011 | 7784.133214 |
| 1792 | Libya | LBY | 2010 | 11611.358595 |
| 1793 | Liechtenstein | LIE | 2020 | 165287.186767 |
| 1794 | Liechtenstein | LIE | 2019 | 167259.160312 |
| 1795 | Liechtenstein | LIE | 2018 | 175286.679025 |
| 1796 | Liechtenstein | LIE | 2017 | 170875.682067 |
| 1797 | Liechtenstein | LIE | 2016 | 165845.995201 |
| 1798 | Liechtenstein | LIE | 2015 | 167809.269875 |
| 1799 | Liechtenstein | LIE | 2014 | 179467.516167 |
| 1800 | Liechtenstein | LIE | 2013 | 173659.411799 |
| 1801 | Liechtenstein | LIE | 2012 | 149461.785571 |
| 1802 | Liechtenstein | LIE | 2011 | 158603.608967 |
| 1803 | Liechtenstein | LIE | 2010 | 141466.827324 |
| 1804 | Lithuania | LTU | 2020 | 20381.855783 |
| 1805 | Lithuania | LTU | 2019 | 19615.549145 |
| 1806 | Lithuania | LTU | 2018 | 19186.359592 |
| 1807 | Lithuania | LTU | 2017 | 16885.407395 |
| 1808 | Lithuania | LTU | 2016 | 15008.313245 |
| 1809 | Lithuania | LTU | 2015 | 14263.964577 |
| 1810 | Lithuania | LTU | 2014 | 16551.018202 |
| 1811 | Lithuania | LTU | 2013 | 15729.652467 |
| 1812 | Lithuania | LTU | 2012 | 14367.709425 |
| 1813 | Lithuania | LTU | 2011 | 14376.947864 |
| 1814 | Lithuania | LTU | 2010 | 11987.508412 |
| 1815 | Luxembourg | LUX | 2020 | 116905.370397 |
| 1816 | Luxembourg | LUX | 2019 | 112726.439673 |
| 1817 | Luxembourg | LUX | 2018 | 116786.511655 |
| 1818 | Luxembourg | LUX | 2017 | 110193.213797 |
| 1819 | Luxembourg | LUX | 2016 | 106899.293550 |
| 1820 | Luxembourg | LUX | 2015 | 105462.012584 |
| 1821 | Luxembourg | LUX | 2014 | 123678.702143 |
| 1822 | Luxembourg | LUX | 2013 | 120000.140730 |
| 1823 | Luxembourg | LUX | 2012 | 112584.676271 |
| 1824 | Luxembourg | LUX | 2011 | 119025.057203 |
| 1825 | Luxembourg | LUX | 2010 | 110885.991379 |
| 1826 | Macao SAR, China | MAC | 2020 | 37474.734595 |
| 1827 | Macao SAR, China | MAC | 2019 | 82998.636101 |
| 1828 | Macao SAR, China | MAC | 2018 | 84779.453694 |
| 1829 | Macao SAR, China | MAC | 2017 | 78896.274749 |
| 1830 | Macao SAR, China | MAC | 2016 | 71919.054919 |
| 1831 | Macao SAR, China | MAC | 2015 | 73220.635555 |
| 1832 | Macao SAR, China | MAC | 2014 | 90873.602487 |
| 1833 | Macao SAR, China | MAC | 2013 | 86853.477047 |
| 1834 | Macao SAR, China | MAC | 2012 | 74111.601186 |
| 1835 | Macao SAR, China | MAC | 2011 | 64528.362823 |
| 1836 | Macao SAR, China | MAC | 2010 | 50676.387082 |
| 1837 | Madagascar | MDG | 2020 | 462.404229 |
| 1838 | Madagascar | MDG | 2019 | 512.279666 |
| 1839 | Madagascar | MDG | 2018 | 512.543992 |
| 1840 | Madagascar | MDG | 2017 | 503.498059 |
| 1841 | Madagascar | MDG | 2016 | 464.616158 |
| 1842 | Madagascar | MDG | 2015 | 455.638035 |
| 1843 | Madagascar | MDG | 2014 | 517.136183 |
| 1844 | Madagascar | MDG | 2013 | 526.688020 |
| 1845 | Madagascar | MDG | 2012 | 504.173738 |
| 1846 | Madagascar | MDG | 2011 | 516.902539 |
| 1847 | Madagascar | MDG | 2010 | 459.375408 |
| 1848 | Malawi | MWI | 2020 | 622.184591 |
| 1849 | Malawi | MWI | 2019 | 584.362867 |
| 1850 | Malawi | MWI | 2018 | 537.932204 |
| 1851 | Malawi | MWI | 2017 | 500.165547 |
| 1852 | Malawi | MWI | 2016 | 454.443266 |
| 1853 | Malawi | MWI | 2015 | 544.276873 |
| 1854 | Malawi | MWI | 2014 | 534.126977 |
| 1855 | Malawi | MWI | 2013 | 501.197173 |
| 1856 | Malawi | MWI | 2012 | 563.061540 |
| 1857 | Malawi | MWI | 2011 | 769.052599 |
| 1858 | Malawi | MWI | 2010 | 688.139191 |
| 1859 | Malaysia | MYS | 2020 | 10164.344431 |
| 1860 | Malaysia | MYS | 2019 | 11132.102743 |
| 1861 | Malaysia | MYS | 2018 | 11073.978970 |
| 1862 | Malaysia | MYS | 2017 | 9979.704473 |
| 1863 | Malaysia | MYS | 2016 | 9555.669593 |
| 1864 | Malaysia | MYS | 2015 | 9699.600463 |
| 1865 | Malaysia | MYS | 2014 | 11045.580121 |
| 1866 | Malaysia | MYS | 2013 | 10727.669022 |
| 1867 | Malaysia | MYS | 2012 | 10601.510456 |
| 1868 | Malaysia | MYS | 2011 | 10209.371945 |
| 1869 | Malaysia | MYS | 2010 | 8880.145805 |
| 1870 | Maldives | MDV | 2020 | 7216.816371 |
| 1871 | Maldives | MDV | 2019 | 11349.859264 |
| 1872 | Maldives | MDV | 2018 | 11034.723597 |
| 1873 | Maldives | MDV | 2017 | 10194.746148 |
| 1874 | Maldives | MDV | 2016 | 9708.141348 |
| 1875 | Maldives | MDV | 2015 | 9480.431514 |
| 1876 | Maldives | MDV | 2014 | 8872.128379 |
| 1877 | Maldives | MDV | 2013 | 8222.558036 |
| 1878 | Maldives | MDV | 2012 | 7447.415605 |
| 1879 | Maldives | MDV | 2011 | 7409.331903 |
| 1880 | Maldives | MDV | 2010 | 7158.061421 |
| 1881 | Mali | MLI | 2020 | 822.906137 |
| 1882 | Mali | MLI | 2019 | 840.175746 |
| 1883 | Mali | MLI | 2018 | 856.356597 |
| 1884 | Mali | MLI | 2017 | 795.682802 |
| 1885 | Mali | MLI | 2016 | 750.051809 |
| 1886 | Mali | MLI | 2015 | 723.504205 |
| 1887 | Mali | MLI | 2014 | 818.430341 |
| 1888 | Mali | MLI | 2013 | 778.797053 |
| 1889 | Mali | MLI | 2012 | 753.392138 |
| 1890 | Mali | MLI | 2011 | 810.182556 |
| 1891 | Mali | MLI | 2010 | 688.327866 |
| 1892 | Malta | MLT | 2020 | 29597.636163 |
| 1893 | Malta | MLT | 2019 | 31727.007075 |
| 1894 | Malta | MLT | 2018 | 31785.884830 |
| 1895 | Malta | MLT | 2017 | 28813.185340 |
| 1896 | Malta | MLT | 2016 | 25623.941632 |
| 1897 | Malta | MLT | 2015 | 24921.714177 |
| 1898 | Malta | MLT | 2014 | 26753.273383 |
| 1899 | Malta | MLT | 2013 | 24769.596229 |
| 1900 | Malta | MLT | 2012 | 22526.537021 |
| 1901 | Malta | MLT | 2011 | 23155.103527 |
| 1902 | Malta | MLT | 2010 | 21798.914294 |
| 1903 | Marshall Islands | MHL | 2020 | 5545.600267 |
| 1904 | Marshall Islands | MHL | 2019 | 5186.833842 |
| 1905 | Marshall Islands | MHL | 2018 | 4771.359204 |
| 1906 | Marshall Islands | MHL | 2017 | 4507.622862 |
| 1907 | Marshall Islands | MHL | 2016 | 4153.117176 |
| 1908 | Marshall Islands | MHL | 2015 | 3703.649059 |
| 1909 | Marshall Islands | MHL | 2014 | 3672.680934 |
| 1910 | Marshall Islands | MHL | 2013 | 3611.699642 |
| 1911 | Marshall Islands | MHL | 2012 | 3445.315403 |
| 1912 | Marshall Islands | MHL | 2011 | 3238.887316 |
| 1913 | Marshall Islands | MHL | 2010 | 3001.319829 |
| 1914 | Mauritania | MRT | 2020 | 1836.292411 |
| 1915 | Mauritania | MRT | 2019 | 1800.875187 |
| 1916 | Mauritania | MRT | 2018 | 1749.954236 |
| 1917 | Mauritania | MRT | 2017 | 1634.642158 |
| 1918 | Mauritania | MRT | 2016 | 1579.200717 |
| 1919 | Mauritania | MRT | 2015 | 1562.726836 |
| 1920 | Mauritania | MRT | 2014 | 1715.388838 |
| 1921 | Mauritania | MRT | 2013 | 1929.775639 |
| 1922 | Mauritania | MRT | 2012 | 1850.384968 |
| 1923 | Mauritania | MRT | 2011 | 1919.452271 |
| 1924 | Mauritania | MRT | 2010 | 1646.130428 |
| 1925 | Mauritius | MUS | 2020 | 9011.042884 |
| 1926 | Mauritius | MUS | 2019 | 11403.252787 |
| 1927 | Mauritius | MUS | 2018 | 11643.460596 |
| 1928 | Mauritius | MUS | 2017 | 10841.684775 |
| 1929 | Mauritius | MUS | 2016 | 9965.725311 |
| 1930 | Mauritius | MUS | 2015 | 9507.871337 |
| 1931 | Mauritius | MUS | 2014 | 10366.355075 |
| 1932 | Mauritius | MUS | 2013 | 9764.644131 |
| 1933 | Mauritius | MUS | 2012 | 9291.236276 |
| 1934 | Mauritius | MUS | 2011 | 9197.042991 |
| 1935 | Mauritius | MUS | 2010 | 8000.376432 |
| 1936 | Mexico | MEX | 2020 | 8894.890650 |
| 1937 | Mexico | MEX | 2019 | 10434.578365 |
| 1938 | Mexico | MEX | 2018 | 10130.320698 |
| 1939 | Mexico | MEX | 2017 | 9693.330091 |
| 1940 | Mexico | MEX | 2016 | 9152.737223 |
| 1941 | Mexico | MEX | 2015 | 10098.173181 |
| 1942 | Mexico | MEX | 2014 | 11490.021690 |
| 1943 | Mexico | MEX | 2013 | 11317.491061 |
| 1944 | Mexico | MEX | 2012 | 10842.733089 |
| 1945 | Mexico | MEX | 2011 | 10766.609939 |
| 1946 | Mexico | MEX | 2010 | 9823.164076 |
| 1947 | Micronesia, Fed. Sts. | FSM | 2020 | 3639.412699 |
| 1948 | Micronesia, Fed. Sts. | FSM | 2019 | 3734.994927 |
| 1949 | Micronesia, Fed. Sts. | FSM | 2018 | 3623.329337 |
| 1950 | Micronesia, Fed. Sts. | FSM | 2017 | 3320.354976 |
| 1951 | Micronesia, Fed. Sts. | FSM | 2016 | 3022.653627 |
| 1952 | Micronesia, Fed. Sts. | FSM | 2015 | 2891.322103 |
| 1953 | Micronesia, Fed. Sts. | FSM | 2014 | 2928.448782 |
| 1954 | Micronesia, Fed. Sts. | FSM | 2013 | 2920.700863 |
| 1955 | Micronesia, Fed. Sts. | FSM | 2012 | 3023.585446 |
| 1956 | Micronesia, Fed. Sts. | FSM | 2011 | 2885.441249 |
| 1957 | Micronesia, Fed. Sts. | FSM | 2010 | 2760.011340 |
| 1958 | Moldova | MDA | 2020 | 4376.242493 |
| 1959 | Moldova | MDA | 2019 | 4404.950422 |
| 1960 | Moldova | MDA | 2018 | 4156.957500 |
| 1961 | Moldova | MDA | 2017 | 3454.954690 |
| 1962 | Moldova | MDA | 2016 | 2847.635069 |
| 1963 | Moldova | MDA | 2015 | 2749.913038 |
| 1964 | Moldova | MDA | 2014 | 3289.167846 |
| 1965 | Moldova | MDA | 2013 | 3321.043978 |
| 1966 | Moldova | MDA | 2012 | 3044.808432 |
| 1967 | Moldova | MDA | 2011 | 2941.362241 |
| 1968 | Moldova | MDA | 2010 | 2436.799351 |
| 1969 | Monaco | MCO | 2020 | 182537.387370 |
| 1970 | Monaco | MCO | 2019 | 199382.838585 |
| 1971 | Monaco | MCO | 2018 | 193968.090133 |
| 1972 | Monaco | MCO | 2017 | 173611.687860 |
| 1973 | Monaco | MCO | 2016 | 174412.494536 |
| 1974 | Monaco | MCO | 2015 | 170338.680381 |
| 1975 | Monaco | MCO | 2014 | 195772.724262 |
| 1976 | Monaco | MCO | 2013 | 185055.517569 |
| 1977 | Monaco | MCO | 2012 | 165497.097810 |
| 1978 | Monaco | MCO | 2011 | 179369.268180 |
| 1979 | Monaco | MCO | 2010 | 161780.745361 |
| 1980 | Mongolia | MNG | 2020 | 4041.174146 |
| 1981 | Mongolia | MNG | 2019 | 4394.947150 |
| 1982 | Mongolia | MNG | 2018 | 4165.022821 |
| 1983 | Mongolia | MNG | 2017 | 3708.248221 |
| 1984 | Mongolia | MNG | 2016 | 3690.756778 |
| 1985 | Mongolia | MNG | 2015 | 3919.351213 |
| 1986 | Mongolia | MNG | 2014 | 4211.939436 |
| 1987 | Mongolia | MNG | 2013 | 4422.300876 |
| 1988 | Mongolia | MNG | 2012 | 4402.304523 |
| 1989 | Mongolia | MNG | 2011 | 3793.743655 |
| 1990 | Mongolia | MNG | 2010 | 2660.288175 |
| 1991 | Montenegro | MNE | 2020 | 7677.371321 |
| 1992 | Montenegro | MNE | 2019 | 8909.653876 |
| 1993 | Montenegro | MNE | 2018 | 8850.374925 |
| 1994 | Montenegro | MNE | 2017 | 7803.358245 |
| 1995 | Montenegro | MNE | 2016 | 7033.439624 |
| 1996 | Montenegro | MNE | 2015 | 6517.192675 |
| 1997 | Montenegro | MNE | 2014 | 7387.872969 |
| 1998 | Montenegro | MNE | 2013 | 7188.863616 |
| 1999 | Montenegro | MNE | 2012 | 6586.399703 |
| 2000 | Montenegro | MNE | 2011 | 7328.789431 |
| 2001 | Montenegro | MNE | 2010 | 6688.402596 |
| 2002 | Morocco | MAR | 2020 | 3258.269043 |
| 2003 | Morocco | MAR | 2019 | 3498.582764 |
| 2004 | Morocco | MAR | 2018 | 3492.672607 |
| 2005 | Morocco | MAR | 2017 | 3288.502686 |
| 2006 | Morocco | MAR | 2016 | 3132.952148 |
| 2007 | Morocco | MAR | 2015 | 3139.228271 |
| 2008 | Morocco | MAR | 2014 | 3430.534424 |
| 2009 | Morocco | MAR | 2013 | 3377.643555 |
| 2010 | Morocco | MAR | 2012 | 3164.004639 |
| 2011 | Morocco | MAR | 2011 | 3302.453125 |
| 2012 | Morocco | MAR | 2010 | 3067.851807 |
| 2013 | Mozambique | MOZ | 2020 | 456.581929 |
| 2014 | Mozambique | MOZ | 2019 | 512.215764 |
| 2015 | Mozambique | MOZ | 2018 | 510.379996 |
| 2016 | Mozambique | MOZ | 2017 | 464.294721 |
| 2017 | Mozambique | MOZ | 2016 | 435.760991 |
| 2018 | Mozambique | MOZ | 2015 | 603.838514 |
| 2019 | Mozambique | MOZ | 2014 | 690.443218 |
| 2020 | Mozambique | MOZ | 2013 | 681.065114 |
| 2021 | Mozambique | MOZ | 2012 | 681.492129 |
| 2022 | Mozambique | MOZ | 2011 | 615.278660 |
| 2023 | Mozambique | MOZ | 2010 | 494.584022 |
| 2024 | Myanmar | MMR | 2020 | 1479.613689 |
| 2025 | Myanmar | MMR | 2019 | 1415.379676 |
| 2026 | Myanmar | MMR | 2018 | 1288.418087 |
| 2027 | Myanmar | MMR | 2017 | 1263.285263 |
| 2028 | Myanmar | MMR | 2016 | 1218.217034 |
| 2029 | Myanmar | MMR | 2015 | 1159.340201 |
| 2030 | Myanmar | MMR | 2014 | 1281.438718 |
| 2031 | Myanmar | MMR | 2013 | 1189.964765 |
| 2032 | Myanmar | MMR | 2012 | 1193.547649 |
| 2033 | Myanmar | MMR | 2011 | 1204.496472 |
| 2034 | Myanmar | MMR | 2010 | 1003.033455 |
| 2035 | Namibia | NAM | 2020 | 4252.041720 |
| 2036 | Namibia | NAM | 2019 | 5126.176143 |
| 2037 | Namibia | NAM | 2018 | 5687.381043 |
| 2038 | Namibia | NAM | 2017 | 5453.570623 |
| 2039 | Namibia | NAM | 2016 | 4614.892075 |
| 2040 | Namibia | NAM | 2015 | 4965.672765 |
| 2041 | Namibia | NAM | 2014 | 5544.104068 |
| 2042 | Namibia | NAM | 2013 | 5463.031366 |
| 2043 | Namibia | NAM | 2012 | 6017.178365 |
| 2044 | Namibia | NAM | 2011 | 5873.059381 |
| 2045 | Namibia | NAM | 2010 | 5445.420063 |
| 2046 | Nauru | NRU | 2020 | 10124.700622 |
| 2047 | Nauru | NRU | 2019 | 10316.527823 |
| 2048 | Nauru | NRU | 2018 | 10985.874397 |
| 2049 | Nauru | NRU | 2017 | 9361.037397 |
| 2050 | Nauru | NRU | 2016 | 8528.630151 |
| 2051 | Nauru | NRU | 2015 | 7587.254410 |
| 2052 | Nauru | NRU | 2014 | 9063.002230 |
| 2053 | Nauru | NRU | 2013 | 8825.978581 |
| 2054 | Nauru | NRU | 2012 | 9675.959685 |
| 2055 | Nauru | NRU | 2011 | 6328.102672 |
| 2056 | Nauru | NRU | 2010 | 4644.355494 |
| 2057 | Nepal | NPL | 2020 | 1139.189892 |
| 2058 | Nepal | NPL | 2019 | 1185.682318 |
| 2059 | Nepal | NPL | 2018 | 1161.534350 |
| 2060 | Nepal | NPL | 2017 | 1027.965474 |
| 2061 | Nepal | NPL | 2016 | 880.224894 |
| 2062 | Nepal | NPL | 2015 | 882.307663 |
| 2063 | Nepal | NPL | 2014 | 827.744705 |
| 2064 | Nepal | NPL | 2013 | 809.384458 |
| 2065 | Nepal | NPL | 2012 | 794.092559 |
| 2066 | Nepal | NPL | 2011 | 791.225577 |
| 2067 | Nepal | NPL | 2010 | 589.165435 |
| 2068 | Netherlands | NLD | 2020 | 52162.570115 |
| 2069 | Netherlands | NLD | 2019 | 52476.273253 |
| 2070 | Netherlands | NLD | 2018 | 53044.532435 |
| 2071 | Netherlands | NLD | 2017 | 48675.222335 |
| 2072 | Netherlands | NLD | 2016 | 46039.105928 |
| 2073 | Netherlands | NLD | 2015 | 45193.403219 |
| 2074 | Netherlands | NLD | 2014 | 52900.537415 |
| 2075 | Netherlands | NLD | 2013 | 52198.897561 |
| 2076 | Netherlands | NLD | 2012 | 50070.141605 |
| 2077 | Netherlands | NLD | 2011 | 54230.312903 |
| 2078 | Netherlands | NLD | 2010 | 50999.745117 |
| 2079 | New Caledonia | NCL | 2020 | 34877.635635 |
| 2080 | New Caledonia | NCL | 2019 | 34934.579430 |
| 2081 | New Caledonia | NCL | 2018 | 36495.195942 |
| 2082 | New Caledonia | NCL | 2017 | 33876.329094 |
| 2083 | New Caledonia | NCL | 2016 | 32286.910498 |
| 2084 | New Caledonia | NCL | 2015 | 32428.572235 |
| 2085 | New Caledonia | NCL | 2014 | 39675.566479 |
| 2086 | New Caledonia | NCL | 2013 | 38503.254061 |
| 2087 | New Caledonia | NCL | 2012 | 37294.022847 |
| 2088 | New Caledonia | NCL | 2011 | 40697.652859 |
| 2089 | New Caledonia | NCL | 2010 | 37494.895203 |
| 2090 | New Zealand | NZL | 2020 | 41760.594784 |
| 2091 | New Zealand | NZL | 2019 | 42796.430582 |
| 2092 | New Zealand | NZL | 2018 | 43236.886692 |
| 2093 | New Zealand | NZL | 2017 | 42910.972836 |
| 2094 | New Zealand | NZL | 2016 | 40058.196162 |
| 2095 | New Zealand | NZL | 2015 | 38630.726589 |
| 2096 | New Zealand | NZL | 2014 | 44572.898754 |
| 2097 | New Zealand | NZL | 2013 | 42976.649588 |
| 2098 | New Zealand | NZL | 2012 | 39973.380759 |
| 2099 | New Zealand | NZL | 2011 | 38387.627078 |
| 2100 | New Zealand | NZL | 2010 | 33676.774124 |
| 2101 | Nicaragua | NIC | 2020 | 1876.607378 |
| 2102 | Nicaragua | NIC | 2019 | 1905.638328 |
| 2103 | Nicaragua | NIC | 2018 | 1981.858367 |
| 2104 | Nicaragua | NIC | 2017 | 2127.282818 |
| 2105 | Nicaragua | NIC | 2016 | 2079.451027 |
| 2106 | Nicaragua | NIC | 2015 | 2025.321432 |
| 2107 | Nicaragua | NIC | 2014 | 1913.521348 |
| 2108 | Nicaragua | NIC | 2013 | 1794.789188 |
| 2109 | Nicaragua | NIC | 2012 | 1746.421254 |
| 2110 | Nicaragua | NIC | 2011 | 1644.801481 |
| 2111 | Nicaragua | NIC | 2010 | 1495.733754 |
| 2112 | Niger | NER | 2020 | 564.841662 |
| 2113 | Niger | NER | 2019 | 549.816128 |
| 2114 | Niger | NER | 2018 | 568.599660 |
| 2115 | Niger | NER | 2017 | 514.543398 |
| 2116 | Niger | NER | 2016 | 497.036121 |
| 2117 | Niger | NER | 2015 | 481.111301 |
| 2118 | Niger | NER | 2014 | 560.754475 |
| 2119 | Niger | NER | 2013 | 548.157849 |
| 2120 | Niger | NER | 2012 | 525.047285 |
| 2121 | Niger | NER | 2011 | 507.602495 |
| 2122 | Niger | NER | 2010 | 471.612688 |
| 2123 | Nigeria | NGA | 2020 | 2074.613747 |
| 2124 | Nigeria | NGA | 2019 | 2334.023643 |
| 2125 | Nigeria | NGA | 2018 | 2125.834491 |
| 2126 | Nigeria | NGA | 2017 | 1941.879479 |
| 2127 | Nigeria | NGA | 2016 | 2144.780344 |
| 2128 | Nigeria | NGA | 2015 | 2679.554223 |
| 2129 | Nigeria | NGA | 2014 | 3200.952799 |
| 2130 | Nigeria | NGA | 2013 | 2976.756832 |
| 2131 | Nigeria | NGA | 2012 | 2728.022788 |
| 2132 | Nigeria | NGA | 2011 | 2504.879101 |
| 2133 | Nigeria | NGA | 2010 | 2280.111289 |
| 2134 | North Macedonia | MKD | 2020 | 5965.450232 |
| 2135 | North Macedonia | MKD | 2019 | 6070.388054 |
| 2136 | North Macedonia | MKD | 2018 | 6108.739170 |
| 2137 | North Macedonia | MKD | 2017 | 5450.497069 |
| 2138 | North Macedonia | MKD | 2016 | 5149.586764 |
| 2139 | North Macedonia | MKD | 2015 | 4861.556160 |
| 2140 | North Macedonia | MKD | 2014 | 5495.731380 |
| 2141 | North Macedonia | MKD | 2013 | 5241.053601 |
| 2142 | North Macedonia | MKD | 2012 | 4728.313079 |
| 2143 | North Macedonia | MKD | 2011 | 5098.094701 |
| 2144 | North Macedonia | MKD | 2010 | 4577.689543 |
| 2145 | Northern Mariana Islands | MNP | 2020 | 17302.922137 |
| 2146 | Northern Mariana Islands | MNP | 2019 | 23687.271852 |
| 2147 | Northern Mariana Islands | MNP | 2018 | 25862.754453 |
| 2148 | Northern Mariana Islands | MNP | 2017 | 30751.641073 |
| 2149 | Northern Mariana Islands | MNP | 2016 | 24054.915612 |
| 2150 | Northern Mariana Islands | MNP | 2015 | 17665.100749 |
| 2151 | Northern Mariana Islands | MNP | 2014 | 16044.430731 |
| 2152 | Northern Mariana Islands | MNP | 2013 | 14806.006789 |
| 2153 | Northern Mariana Islands | MNP | 2012 | 14247.789301 |
| 2154 | Northern Mariana Islands | MNP | 2011 | 13880.426504 |
| 2155 | Northern Mariana Islands | MNP | 2010 | 14772.496164 |
| 2156 | Norway | NOR | 2020 | 68340.018103 |
| 2157 | Norway | NOR | 2019 | 76430.588947 |
| 2158 | Norway | NOR | 2018 | 82792.842711 |
| 2159 | Norway | NOR | 2017 | 76131.838403 |
| 2160 | Norway | NOR | 2016 | 70867.360997 |
| 2161 | Norway | NOR | 2015 | 74809.965805 |
| 2162 | Norway | NOR | 2014 | 97666.695184 |
| 2163 | Norway | NOR | 2013 | 103553.840134 |
| 2164 | Norway | NOR | 2012 | 102175.919298 |
| 2165 | Norway | NOR | 2011 | 101221.813477 |
| 2166 | Norway | NOR | 2010 | 88163.208593 |
| 2167 | Oman | OMN | 2020 | 16707.623006 |
| 2168 | Oman | OMN | 2019 | 19132.152274 |
| 2169 | Oman | OMN | 2018 | 19887.574311 |
| 2170 | Oman | OMN | 2017 | 17802.575118 |
| 2171 | Oman | OMN | 2016 | 17082.206200 |
| 2172 | Oman | OMN | 2015 | 18777.433059 |
| 2173 | Oman | OMN | 2014 | 23121.206377 |
| 2174 | Oman | OMN | 2013 | 23563.940599 |
| 2175 | Oman | OMN | 2012 | 24722.638825 |
| 2176 | Oman | OMN | 2011 | 24166.096305 |
| 2177 | Oman | OMN | 2010 | 22552.199007 |
| 2178 | Pakistan | PAK | 2020 | 1322.314785 |
| 2179 | Pakistan | PAK | 2019 | 1437.165833 |
| 2180 | Pakistan | PAK | 2018 | 1620.742591 |
| 2181 | Pakistan | PAK | 2017 | 1567.640612 |
| 2182 | Pakistan | PAK | 2016 | 1468.822082 |
| 2183 | Pakistan | PAK | 2015 | 1421.835278 |
| 2184 | Pakistan | PAK | 2014 | 1303.185370 |
| 2185 | Pakistan | PAK | 2013 | 1259.668368 |
| 2186 | Pakistan | PAK | 2012 | 1236.892763 |
| 2187 | Pakistan | PAK | 2011 | 1161.044321 |
| 2188 | Pakistan | PAK | 2010 | 1011.597180 |
| 2189 | Palau | PLW | 2020 | 14349.316819 |
| 2190 | Palau | PLW | 2019 | 15738.467013 |
| 2191 | Palau | PLW | 2018 | 16152.389233 |
| 2192 | Palau | PLW | 2017 | 16011.661154 |
| 2193 | Palau | PLW | 2016 | 16743.376740 |
| 2194 | Palau | PLW | 2015 | 15761.363381 |
| 2195 | Palau | PLW | 2014 | 13580.006743 |
| 2196 | Palau | PLW | 2013 | 12418.826172 |
| 2197 | Palau | PLW | 2012 | 11835.383930 |
| 2198 | Palau | PLW | 2011 | 10795.564693 |
| 2199 | Palau | PLW | 2010 | 10029.288026 |
| 2200 | Panama | PAN | 2020 | 13293.333195 |
| 2201 | Panama | PAN | 2019 | 16472.831747 |
| 2202 | Panama | PAN | 2018 | 16156.074286 |
| 2203 | Panama | PAN | 2017 | 15185.972481 |
| 2204 | Panama | PAN | 2016 | 14382.232382 |
| 2205 | Panama | PAN | 2015 | 13669.559442 |
| 2206 | Panama | PAN | 2014 | 12837.247958 |
| 2207 | Panama | PAN | 2013 | 11932.286221 |
| 2208 | Panama | PAN | 2012 | 10767.293179 |
| 2209 | Panama | PAN | 2011 | 9403.439908 |
| 2210 | Panama | PAN | 2010 | 8124.558307 |
| 2211 | Papua New Guinea | PNG | 2020 | 2446.084687 |
| 2212 | Papua New Guinea | PNG | 2019 | 2593.775554 |
| 2213 | Papua New Guinea | PNG | 2018 | 2584.327802 |
| 2214 | Papua New Guinea | PNG | 2017 | 2495.140773 |
| 2215 | Papua New Guinea | PNG | 2016 | 2332.675888 |
| 2216 | Papua New Guinea | PNG | 2015 | 2502.073445 |
| 2217 | Papua New Guinea | PNG | 2014 | 2742.250050 |
| 2218 | Papua New Guinea | PNG | 2013 | 2578.498647 |
| 2219 | Papua New Guinea | PNG | 2012 | 2653.092790 |
| 2220 | Papua New Guinea | PNG | 2011 | 2303.826611 |
| 2221 | Papua New Guinea | PNG | 2010 | 1879.240559 |
| 2222 | Paraguay | PRY | 2020 | 5353.348065 |
| 2223 | Paraguay | PRY | 2019 | 5807.838794 |
| 2224 | Paraguay | PRY | 2018 | 6242.961454 |
| 2225 | Paraguay | PRY | 2017 | 6136.058301 |
| 2226 | Paraguay | PRY | 2016 | 5759.042198 |
| 2227 | Paraguay | PRY | 2015 | 5861.401895 |
| 2228 | Paraguay | PRY | 2014 | 6629.416993 |
| 2229 | Paraguay | PRY | 2013 | 6410.814703 |
| 2230 | Paraguay | PRY | 2012 | 5617.104918 |
| 2231 | Paraguay | PRY | 2011 | 5776.281848 |
| 2232 | Paraguay | PRY | 2010 | 4725.726341 |
| 2233 | Peru | PER | 2020 | 6063.626923 |
| 2234 | Peru | PER | 2019 | 6955.880824 |
| 2235 | Peru | PER | 2018 | 6912.103988 |
| 2236 | Peru | PER | 2017 | 6676.308793 |
| 2237 | Peru | PER | 2016 | 6163.860425 |
| 2238 | Peru | PER | 2015 | 6180.119268 |
| 2239 | Peru | PER | 2014 | 6614.830820 |
| 2240 | Peru | PER | 2013 | 6697.187747 |
| 2241 | Peru | PER | 2012 | 6475.720443 |
| 2242 | Peru | PER | 2011 | 5826.832307 |
| 2243 | Peru | PER | 2010 | 5047.204643 |
| 2244 | Philippines | PHL | 2020 | 3224.422811 |
| 2245 | Philippines | PHL | 2019 | 3413.849044 |
| 2246 | Philippines | PHL | 2018 | 3194.672701 |
| 2247 | Philippines | PHL | 2017 | 3077.434419 |
| 2248 | Philippines | PHL | 2016 | 3038.152037 |
| 2249 | Philippines | PHL | 2015 | 2974.296917 |
| 2250 | Philippines | PHL | 2014 | 2935.928598 |
| 2251 | Philippines | PHL | 2013 | 2847.567943 |
| 2252 | Philippines | PHL | 2012 | 2671.777522 |
| 2253 | Philippines | PHL | 2011 | 2431.199961 |
| 2254 | Philippines | PHL | 2010 | 2201.776828 |
| 2255 | Poland | POL | 2020 | 15816.820402 |
| 2256 | Poland | POL | 2019 | 15700.013580 |
| 2257 | Poland | POL | 2018 | 15504.508937 |
| 2258 | Poland | POL | 2017 | 13815.499946 |
| 2259 | Poland | POL | 2016 | 12378.811764 |
| 2260 | Poland | POL | 2015 | 12560.051420 |
| 2261 | Poland | POL | 2014 | 14181.948682 |
| 2262 | Poland | POL | 2013 | 13558.341131 |
| 2263 | Poland | POL | 2012 | 13010.755587 |
| 2264 | Poland | POL | 2011 | 13776.388362 |
| 2265 | Poland | POL | 2010 | 12504.250186 |
| 2266 | Portugal | PRT | 2020 | 22242.406418 |
| 2267 | Portugal | PRT | 2019 | 23330.817289 |
| 2268 | Portugal | PRT | 2018 | 23562.554523 |
| 2269 | Portugal | PRT | 2017 | 21490.429863 |
| 2270 | Portugal | PRT | 2016 | 19991.972488 |
| 2271 | Portugal | PRT | 2015 | 19250.106538 |
| 2272 | Portugal | PRT | 2014 | 22103.700970 |
| 2273 | Portugal | PRT | 2013 | 21653.195975 |
| 2274 | Portugal | PRT | 2012 | 20563.713601 |
| 2275 | Portugal | PRT | 2011 | 23217.295497 |
| 2276 | Portugal | PRT | 2010 | 22520.642312 |
| 2277 | Puerto Rico | PRI | 2020 | 31427.429114 |
| 2278 | Puerto Rico | PRI | 2019 | 32916.866801 |
| 2279 | Puerto Rico | PRI | 2018 | 31615.066792 |
| 2280 | Puerto Rico | PRI | 2017 | 31108.752751 |
| 2281 | Puerto Rico | PRI | 2016 | 30627.163402 |
| 2282 | Puerto Rico | PRI | 2015 | 29763.488301 |
| 2283 | Puerto Rico | PRI | 2014 | 28981.457331 |
| 2284 | Puerto Rico | PRI | 2013 | 28513.165735 |
| 2285 | Puerto Rico | PRI | 2012 | 27944.733894 |
| 2286 | Puerto Rico | PRI | 2011 | 27278.883050 |
| 2287 | Puerto Rico | PRI | 2010 | 26435.748786 |
| 2288 | Qatar | QAT | 2020 | 52315.660078 |
| 2289 | Qatar | QAT | 2019 | 62827.396954 |
| 2290 | Qatar | QAT | 2018 | 66264.081168 |
| 2291 | Qatar | QAT | 2017 | 59407.698050 |
| 2292 | Qatar | QAT | 2016 | 58467.235571 |
| 2293 | Qatar | QAT | 2015 | 66984.910200 |
| 2294 | Qatar | QAT | 2014 | 93126.149463 |
| 2295 | Qatar | QAT | 2013 | 97630.825515 |
| 2296 | Qatar | QAT | 2012 | 98041.362238 |
| 2297 | Qatar | QAT | 2011 | 92992.997131 |
| 2298 | Qatar | QAT | 2010 | 73021.309753 |
| 2299 | Romania | ROU | 2020 | 13047.456656 |
| 2300 | Romania | ROU | 2019 | 12957.999114 |
| 2301 | Romania | ROU | 2018 | 12494.423579 |
| 2302 | Romania | ROU | 2017 | 10727.970863 |
| 2303 | Romania | ROU | 2016 | 9404.381259 |
| 2304 | Romania | ROU | 2015 | 8976.954489 |
| 2305 | Romania | ROU | 2014 | 10031.342153 |
| 2306 | Romania | ROU | 2013 | 9497.206476 |
| 2307 | Romania | ROU | 2012 | 8930.729912 |
| 2308 | Romania | ROU | 2011 | 9560.159425 |
| 2309 | Romania | ROU | 2010 | 8397.809173 |
| 2310 | Russian Federation | RUS | 2020 | 10194.441406 |
| 2311 | Russian Federation | RUS | 2019 | 11536.258789 |
| 2312 | Russian Federation | RUS | 2018 | 11287.354492 |
| 2313 | Russian Federation | RUS | 2017 | 10720.332031 |
| 2314 | Russian Federation | RUS | 2016 | 8704.894531 |
| 2315 | Russian Federation | RUS | 2015 | 9313.021484 |
| 2316 | Russian Federation | RUS | 2014 | 14095.646484 |
| 2317 | Russian Federation | RUS | 2013 | 15974.622070 |
| 2318 | Russian Federation | RUS | 2012 | 15420.859375 |
| 2319 | Russian Federation | RUS | 2011 | 14311.064453 |
| 2320 | Russian Federation | RUS | 2010 | 10674.990234 |
| 2321 | Rwanda | RWA | 2020 | 773.773261 |
| 2322 | Rwanda | RWA | 2019 | 806.100820 |
| 2323 | Rwanda | RWA | 2018 | 768.943661 |
| 2324 | Rwanda | RWA | 2017 | 756.547641 |
| 2325 | Rwanda | RWA | 2016 | 728.869619 |
| 2326 | Rwanda | RWA | 2015 | 733.887473 |
| 2327 | Rwanda | RWA | 2014 | 724.792350 |
| 2328 | Rwanda | RWA | 2013 | 704.485626 |
| 2329 | Rwanda | RWA | 2012 | 706.202004 |
| 2330 | Rwanda | RWA | 2011 | 650.991484 |
| 2331 | Rwanda | RWA | 2010 | 594.160254 |
| 2332 | Samoa | WSM | 2020 | 4042.722752 |
| 2333 | Samoa | WSM | 2019 | 4308.300729 |
| 2334 | Samoa | WSM | 2018 | 4189.052191 |
| 2335 | Samoa | WSM | 2017 | 4261.640343 |
| 2336 | Samoa | WSM | 2016 | 4105.810905 |
| 2337 | Samoa | WSM | 2015 | 4048.467113 |
| 2338 | Samoa | WSM | 2014 | 3948.728022 |
| 2339 | Samoa | WSM | 2013 | 3989.898590 |
| 2340 | Samoa | WSM | 2012 | 3902.311992 |
| 2341 | Samoa | WSM | 2011 | 3789.626995 |
| 2342 | Samoa | WSM | 2010 | 3494.395225 |
| 2343 | San Marino | SMR | 2020 | 45321.489223 |
| 2344 | San Marino | SMR | 2019 | 47287.398395 |
| 2345 | San Marino | SMR | 2018 | 48464.524648 |
| 2346 | San Marino | SMR | 2017 | 44885.517838 |
| 2347 | San Marino | SMR | 2016 | 43398.428526 |
| 2348 | San Marino | SMR | 2015 | 42281.811255 |
| 2349 | San Marino | SMR | 2014 | 50133.606524 |
| 2350 | San Marino | SMR | 2013 | 50435.367330 |
| 2351 | San Marino | SMR | 2012 | 48433.570300 |
| 2352 | San Marino | SMR | 2011 | 55815.285261 |
| 2353 | San Marino | SMR | 2010 | 59516.323399 |
| 2354 | Sao Tome and Principe | STP | 2020 | 2155.265868 |
| 2355 | Sao Tome and Principe | STP | 2019 | 1924.408150 |
| 2356 | Sao Tome and Principe | STP | 2018 | 1815.605495 |
| 2357 | Sao Tome and Principe | STP | 2017 | 1547.822710 |
| 2358 | Sao Tome and Principe | STP | 2016 | 1428.257908 |
| 2359 | Sao Tome and Principe | STP | 2015 | 1292.733055 |
| 2360 | Sao Tome and Principe | STP | 2014 | 1484.170105 |
| 2361 | Sao Tome and Principe | STP | 2013 | 1378.230193 |
| 2362 | Sao Tome and Principe | STP | 2012 | 1207.700702 |
| 2363 | Sao Tome and Principe | STP | 2011 | 1217.212064 |
| 2364 | Sao Tome and Principe | STP | 2010 | 1043.281427 |
| 2365 | Saudi Arabia | SAU | 2020 | 20398.060987 |
| 2366 | Saudi Arabia | SAU | 2019 | 23405.706100 |
| 2367 | Saudi Arabia | SAU | 2018 | 24175.583314 |
| 2368 | Saudi Arabia | SAU | 2017 | 20910.482962 |
| 2369 | Saudi Arabia | SAU | 2016 | 19930.407544 |
| 2370 | Saudi Arabia | SAU | 2015 | 20442.366063 |
| 2371 | Saudi Arabia | SAU | 2014 | 23862.801186 |
| 2372 | Saudi Arabia | SAU | 2013 | 23945.512311 |
| 2373 | Saudi Arabia | SAU | 2012 | 24069.203315 |
| 2374 | Saudi Arabia | SAU | 2011 | 22441.571144 |
| 2375 | Saudi Arabia | SAU | 2010 | 17958.947831 |
| 2376 | Senegal | SEN | 2020 | 1492.475903 |
| 2377 | Senegal | SEN | 2019 | 1462.678353 |
| 2378 | Senegal | SEN | 2018 | 1484.227070 |
| 2379 | Senegal | SEN | 2017 | 1385.199214 |
| 2380 | Senegal | SEN | 2016 | 1290.749971 |
| 2381 | Senegal | SEN | 2015 | 1238.126400 |
| 2382 | Senegal | SEN | 2014 | 1417.094987 |
| 2383 | Senegal | SEN | 2013 | 1391.532190 |
| 2384 | Senegal | SEN | 2012 | 1334.725915 |
| 2385 | Senegal | SEN | 2011 | 1383.539116 |
| 2386 | Senegal | SEN | 2010 | 1286.604966 |
| 2387 | Serbia | SRB | 2020 | 7733.803469 |
| 2388 | Serbia | SRB | 2019 | 7417.206608 |
| 2389 | Serbia | SRB | 2018 | 7252.403668 |
| 2390 | Serbia | SRB | 2017 | 6292.546549 |
| 2391 | Serbia | SRB | 2016 | 5765.203352 |
| 2392 | Serbia | SRB | 2015 | 5588.979444 |
| 2393 | Serbia | SRB | 2014 | 6600.056211 |
| 2394 | Serbia | SRB | 2013 | 6755.073675 |
| 2395 | Serbia | SRB | 2012 | 6015.945228 |
| 2396 | Serbia | SRB | 2011 | 6809.159804 |
| 2397 | Serbia | SRB | 2010 | 5735.422857 |
| 2398 | Seychelles | SYC | 2020 | 12020.021064 |
| 2399 | Seychelles | SYC | 2019 | 16851.119765 |
| 2400 | Seychelles | SYC | 2018 | 16411.921117 |
| 2401 | Seychelles | SYC | 2017 | 15961.243631 |
| 2402 | Seychelles | SYC | 2016 | 15409.804634 |
| 2403 | Seychelles | SYC | 2015 | 14894.485783 |
| 2404 | Seychelles | SYC | 2014 | 15188.174675 |
| 2405 | Seychelles | SYC | 2013 | 14729.626623 |
| 2406 | Seychelles | SYC | 2012 | 12342.510282 |
| 2407 | Seychelles | SYC | 2011 | 12113.881722 |
| 2408 | Seychelles | SYC | 2010 | 10938.152764 |
| 2409 | Sierra Leone | SLE | 2020 | 493.432241 |
| 2410 | Sierra Leone | SLE | 2019 | 506.606914 |
| 2411 | Sierra Leone | SLE | 2018 | 519.649964 |
| 2412 | Sierra Leone | SLE | 2017 | 484.456129 |
| 2413 | Sierra Leone | SLE | 2016 | 515.447840 |
| 2414 | Sierra Leone | SLE | 2015 | 581.293412 |
| 2415 | Sierra Leone | SLE | 2014 | 702.338588 |
| 2416 | Sierra Leone | SLE | 2013 | 706.452682 |
| 2417 | Sierra Leone | SLE | 2012 | 558.179723 |
| 2418 | Sierra Leone | SLE | 2011 | 443.451842 |
| 2419 | Sierra Leone | SLE | 2010 | 400.540744 |
| 2420 | Singapore | SGP | 2020 | 61273.991659 |
| 2421 | Singapore | SGP | 2019 | 66070.486812 |
| 2422 | Singapore | SGP | 2018 | 66836.521995 |
| 2423 | Singapore | SGP | 2017 | 61164.897357 |
| 2424 | Singapore | SGP | 2016 | 56895.658313 |
| 2425 | Singapore | SGP | 2015 | 55645.606861 |
| 2426 | Singapore | SGP | 2014 | 57564.802311 |
| 2427 | Singapore | SGP | 2013 | 56967.425794 |
| 2428 | Singapore | SGP | 2012 | 55547.555308 |
| 2429 | Singapore | SGP | 2011 | 53891.457026 |
| 2430 | Singapore | SGP | 2010 | 47236.683085 |
| 2431 | Sint Maarten (Dutch part) | SXM | 2020 | 29223.069615 |
| 2432 | Sint Maarten (Dutch part) | SXM | 2019 | 33836.773350 |
| 2433 | Sint Maarten (Dutch part) | SXM | 2018 | 30791.061076 |
| 2434 | Sint Maarten (Dutch part) | SXM | 2017 | 33351.706547 |
| 2435 | Sint Maarten (Dutch part) | SXM | 2016 | 35703.099949 |
| 2436 | Sint Maarten (Dutch part) | SXM | 2015 | 36519.992587 |
| 2437 | Sint Maarten (Dutch part) | SXM | 2014 | 36136.699504 |
| 2438 | Sint Maarten (Dutch part) | SXM | 2013 | 27942.880540 |
| 2439 | Sint Maarten (Dutch part) | SXM | 2012 | 28460.332615 |
| 2440 | Sint Maarten (Dutch part) | SXM | 2011 | 27997.289830 |
| 2441 | Sint Maarten (Dutch part) | SXM | 2010 | NaN |
| 2442 | Slovak Republic | SVK | 2020 | 19552.091110 |
| 2443 | Slovak Republic | SVK | 2019 | 19381.890547 |
| 2444 | Slovak Republic | SVK | 2018 | 19486.393685 |
| 2445 | Slovak Republic | SVK | 2017 | 17585.197002 |
| 2446 | Slovak Republic | SVK | 2016 | 16563.440497 |
| 2447 | Slovak Republic | SVK | 2015 | 16390.882175 |
| 2448 | Slovak Republic | SVK | 2014 | 18719.988141 |
| 2449 | Slovak Republic | SVK | 2013 | 18276.009552 |
| 2450 | Slovak Republic | SVK | 2012 | 17498.353900 |
| 2451 | Slovak Republic | SVK | 2011 | 18509.740216 |
| 2452 | Slovak Republic | SVK | 2010 | 16908.847956 |
| 2453 | Slovenia | SVN | 2020 | 25558.429054 |
| 2454 | Slovenia | SVN | 2019 | 26042.446347 |
| 2455 | Slovenia | SVN | 2018 | 26123.747128 |
| 2456 | Slovenia | SVN | 2017 | 23514.025460 |
| 2457 | Slovenia | SVN | 2016 | 21678.359467 |
| 2458 | Slovenia | SVN | 2015 | 20890.166430 |
| 2459 | Slovenia | SVN | 2014 | 24247.173318 |
| 2460 | Slovenia | SVN | 2013 | 23503.282485 |
| 2461 | Slovenia | SVN | 2012 | 22641.805123 |
| 2462 | Slovenia | SVN | 2011 | 25128.015043 |
| 2463 | Slovenia | SVN | 2010 | 23532.480855 |
| 2464 | Solomon Islands | SLB | 2020 | 2222.462119 |
| 2465 | Solomon Islands | SLB | 2019 | 2398.773050 |
| 2466 | Solomon Islands | SLB | 2018 | 2450.482888 |
| 2467 | Solomon Islands | SLB | 2017 | 2283.579051 |
| 2468 | Solomon Islands | SLB | 2016 | 2196.283891 |
| 2469 | Solomon Islands | SLB | 2015 | 2134.805418 |
| 2470 | Solomon Islands | SLB | 2014 | 2235.733703 |
| 2471 | Solomon Islands | SLB | 2013 | 2208.085284 |
| 2472 | Solomon Islands | SLB | 2012 | 2087.517887 |
| 2473 | Solomon Islands | SLB | 2011 | 1921.356352 |
| 2474 | Solomon Islands | SLB | 2010 | 1661.997885 |
| 2475 | Somalia | SOM | 2020 | 556.578066 |
| 2476 | Somalia | SOM | 2019 | 589.465892 |
| 2477 | Somalia | SOM | 2018 | 537.159290 |
| 2478 | Somalia | SOM | 2017 | 555.185124 |
| 2479 | Somalia | SOM | 2016 | 517.097582 |
| 2480 | Somalia | SOM | 2015 | 507.482915 |
| 2481 | Somalia | SOM | 2014 | 491.189804 |
| 2482 | Somalia | SOM | 2013 | 454.077264 |
| 2483 | Somalia | SOM | 2012 | NaN |
| 2484 | Somalia | SOM | 2011 | NaN |
| 2485 | Somalia | SOM | 2010 | NaN |
| 2486 | South Africa | ZAF | 2020 | 5753.066494 |
| 2487 | South Africa | ZAF | 2019 | 6702.526617 |
| 2488 | South Africa | ZAF | 2018 | 7067.724165 |
| 2489 | South Africa | ZAF | 2017 | 6734.475153 |
| 2490 | South Africa | ZAF | 2016 | 5735.066787 |
| 2491 | South Africa | ZAF | 2015 | 6204.929901 |
| 2492 | South Africa | ZAF | 2014 | 6965.137897 |
| 2493 | South Africa | ZAF | 2013 | 7441.230854 |
| 2494 | South Africa | ZAF | 2012 | 8173.869138 |
| 2495 | South Africa | ZAF | 2011 | 8737.041269 |
| 2496 | South Africa | ZAF | 2010 | 8059.562798 |
| 2497 | South Sudan | SSD | 2020 | NaN |
| 2498 | South Sudan | SSD | 2019 | NaN |
| 2499 | South Sudan | SSD | 2018 | NaN |
| 2500 | South Sudan | SSD | 2017 | NaN |
| 2501 | South Sudan | SSD | 2016 | NaN |
| 2502 | South Sudan | SSD | 2015 | 1071.777765 |
| 2503 | South Sudan | SSD | 2014 | 1245.149311 |
| 2504 | South Sudan | SSD | 2013 | 1659.140787 |
| 2505 | South Sudan | SSD | 2012 | 1114.923723 |
| 2506 | South Sudan | SSD | 2011 | 1455.358407 |
| 2507 | South Sudan | SSD | 2010 | 1503.133889 |
| 2508 | Spain | ESP | 2020 | 26984.296277 |
| 2509 | Spain | ESP | 2019 | 29581.518551 |
| 2510 | Spain | ESP | 2018 | 30379.721113 |
| 2511 | Spain | ESP | 2017 | 28185.321367 |
| 2512 | Spain | ESP | 2016 | 26537.159489 |
| 2513 | Spain | ESP | 2015 | 25754.361029 |
| 2514 | Spain | ESP | 2014 | 29513.651180 |
| 2515 | Spain | ESP | 2013 | 29077.182056 |
| 2516 | Spain | ESP | 2012 | 28322.946592 |
| 2517 | Spain | ESP | 2011 | 31677.900308 |
| 2518 | Spain | ESP | 2010 | 30532.480508 |
| 2519 | Sri Lanka | LKA | 2020 | 3852.389091 |
| 2520 | Sri Lanka | LKA | 2019 | 4082.694049 |
| 2521 | Sri Lanka | LKA | 2018 | 4360.584735 |
| 2522 | Sri Lanka | LKA | 2017 | 4388.201906 |
| 2523 | Sri Lanka | LKA | 2016 | 4107.829775 |
| 2524 | Sri Lanka | LKA | 2015 | 3990.353117 |
| 2525 | Sri Lanka | LKA | 2014 | 3885.623616 |
| 2526 | Sri Lanka | LKA | 2013 | 3643.832447 |
| 2527 | Sri Lanka | LKA | 2012 | 3351.892476 |
| 2528 | Sri Lanka | LKA | 2011 | 3248.040210 |
| 2529 | Sri Lanka | LKA | 2010 | 2836.974109 |
| 2530 | St. Kitts and Nevis | KNA | 2020 | 18553.657137 |
| 2531 | St. Kitts and Nevis | KNA | 2019 | 23204.970564 |
| 2532 | St. Kitts and Nevis | KNA | 2018 | 22533.882053 |
| 2533 | St. Kitts and Nevis | KNA | 2017 | 22148.512434 |
| 2534 | St. Kitts and Nevis | KNA | 2016 | 21079.520971 |
| 2535 | St. Kitts and Nevis | KNA | 2015 | 20025.652352 |
| 2536 | St. Kitts and Nevis | KNA | 2014 | 19945.315170 |
| 2537 | St. Kitts and Nevis | KNA | 2013 | 18315.914675 |
| 2538 | St. Kitts and Nevis | KNA | 2012 | 17293.806053 |
| 2539 | St. Kitts and Nevis | KNA | 2011 | 17571.984460 |
| 2540 | St. Kitts and Nevis | KNA | 2010 | 16427.621005 |
| 2541 | St. Lucia | LCA | 2020 | 8951.524766 |
| 2542 | St. Lucia | LCA | 2019 | 11773.427482 |
| 2543 | St. Lucia | LCA | 2018 | 11563.830425 |
| 2544 | St. Lucia | LCA | 2017 | 11270.474710 |
| 2545 | St. Lucia | LCA | 2016 | 10574.386577 |
| 2546 | St. Lucia | LCA | 2015 | 10290.371568 |
| 2547 | St. Lucia | LCA | 2014 | 10007.144510 |
| 2548 | St. Lucia | LCA | 2013 | 9542.713574 |
| 2549 | St. Lucia | LCA | 2012 | 9231.576254 |
| 2550 | St. Lucia | LCA | 2011 | 9110.751810 |
| 2551 | St. Lucia | LCA | 2010 | 8672.215668 |
| 2552 | St. Martin (French part) | MAF | 2020 | NaN |
| 2553 | St. Martin (French part) | MAF | 2019 | 19691.616712 |
| 2554 | St. Martin (French part) | MAF | 2018 | NaN |
| 2555 | St. Martin (French part) | MAF | 2017 | NaN |
| 2556 | St. Martin (French part) | MAF | 2016 | NaN |
| 2557 | St. Martin (French part) | MAF | 2015 | NaN |
| 2558 | St. Martin (French part) | MAF | 2014 | 21920.023781 |
| 2559 | St. Martin (French part) | MAF | 2013 | NaN |
| 2560 | St. Martin (French part) | MAF | 2012 | NaN |
| 2561 | St. Martin (French part) | MAF | 2011 | 21344.587305 |
| 2562 | St. Martin (French part) | MAF | 2010 | NaN |
| 2563 | St. Vincent and the Grenadines | VCT | 2020 | 8306.360493 |
| 2564 | St. Vincent and the Grenadines | VCT | 2019 | 8680.251102 |
| 2565 | St. Vincent and the Grenadines | VCT | 2018 | 8399.707731 |
| 2566 | St. Vincent and the Grenadines | VCT | 2017 | 7996.636984 |
| 2567 | St. Vincent and the Grenadines | VCT | 2016 | 7684.792840 |
| 2568 | St. Vincent and the Grenadines | VCT | 2015 | 7386.746638 |
| 2569 | St. Vincent and the Grenadines | VCT | 2014 | 7210.603113 |
| 2570 | St. Vincent and the Grenadines | VCT | 2013 | 7117.554763 |
| 2571 | St. Vincent and the Grenadines | VCT | 2012 | 6754.370184 |
| 2572 | St. Vincent and the Grenadines | VCT | 2011 | 6566.482713 |
| 2573 | St. Vincent and the Grenadines | VCT | 2010 | 6590.989579 |
| 2574 | Sudan | SDN | 2020 | 608.332520 |
| 2575 | Sudan | SDN | 2019 | 748.010925 |
| 2576 | Sudan | SDN | 2018 | 769.869141 |
| 2577 | Sudan | SDN | 2017 | 1014.842468 |
| 2578 | Sudan | SDN | 2016 | 1082.616577 |
| 2579 | Sudan | SDN | 2015 | 1355.126099 |
| 2580 | Sudan | SDN | 2014 | 1338.173096 |
| 2581 | Sudan | SDN | 2013 | 1195.420288 |
| 2582 | Sudan | SDN | 2012 | 1070.339722 |
| 2583 | Sudan | SDN | 2011 | 1391.425659 |
| 2584 | Sudan | SDN | 2010 | 1356.894653 |
| 2585 | Suriname | SUR | 2020 | 4796.533314 |
| 2586 | Suriname | SUR | 2019 | 6690.044786 |
| 2587 | Suriname | SUR | 2018 | 6730.836961 |
| 2588 | Suriname | SUR | 2017 | 6112.883014 |
| 2589 | Suriname | SUR | 2016 | 5705.399487 |
| 2590 | Suriname | SUR | 2015 | 8907.837258 |
| 2591 | Suriname | SUR | 2014 | 9199.177893 |
| 2592 | Suriname | SUR | 2013 | 9124.541093 |
| 2593 | Suriname | SUR | 2012 | 8922.956186 |
| 2594 | Suriname | SUR | 2011 | 8009.252302 |
| 2595 | Suriname | SUR | 2010 | 7999.507394 |
| 2596 | Sweden | SWE | 2020 | 52837.903978 |
| 2597 | Sweden | SWE | 2019 | 51939.429745 |
| 2598 | Sweden | SWE | 2018 | 54589.060386 |
| 2599 | Sweden | SWE | 2017 | 53791.508730 |
| 2600 | Sweden | SWE | 2016 | 51965.157153 |
| 2601 | Sweden | SWE | 2015 | 51545.483610 |
| 2602 | Sweden | SWE | 2014 | 60020.360458 |
| 2603 | Sweden | SWE | 2013 | 61126.943196 |
| 2604 | Sweden | SWE | 2012 | 58037.821319 |
| 2605 | Sweden | SWE | 2011 | 60755.759551 |
| 2606 | Sweden | SWE | 2010 | 52869.044289 |
| 2607 | Switzerland | CHE | 2020 | 85897.784334 |
| 2608 | Switzerland | CHE | 2019 | 84121.931030 |
| 2609 | Switzerland | CHE | 2018 | 85217.369151 |
| 2610 | Switzerland | CHE | 2017 | 82254.376927 |
| 2611 | Switzerland | CHE | 2016 | 82153.074545 |
| 2612 | Switzerland | CHE | 2015 | 83806.447600 |
| 2613 | Switzerland | CHE | 2014 | 88724.990940 |
| 2614 | Switzerland | CHE | 2013 | 87304.330581 |
| 2615 | Switzerland | CHE | 2012 | 85836.207677 |
| 2616 | Switzerland | CHE | 2011 | 90476.758965 |
| 2617 | Switzerland | CHE | 2010 | 76531.372941 |
| 2618 | Syrian Arab Republic | SYR | 2020 | 537.090235 |
| 2619 | Syrian Arab Republic | SYR | 2019 | 1124.520554 |
| 2620 | Syrian Arab Republic | SYR | 2018 | 1111.872092 |
| 2621 | Syrian Arab Republic | SYR | 2017 | 862.319063 |
| 2622 | Syrian Arab Republic | SYR | 2016 | 664.341672 |
| 2623 | Syrian Arab Republic | SYR | 2015 | 857.497867 |
| 2624 | Syrian Arab Republic | SYR | 2014 | 1071.234204 |
| 2625 | Syrian Arab Republic | SYR | 2013 | 993.739883 |
| 2626 | Syrian Arab Republic | SYR | 2012 | 1910.604539 |
| 2627 | Syrian Arab Republic | SYR | 2011 | 2971.282455 |
| 2628 | Syrian Arab Republic | SYR | 2010 | 11304.644928 |
| 2629 | Tajikistan | TJK | 2020 | 852.330230 |
| 2630 | Tajikistan | TJK | 2019 | 889.023372 |
| 2631 | Tajikistan | TJK | 2018 | 850.666958 |
| 2632 | Tajikistan | TJK | 2017 | 844.365250 |
| 2633 | Tajikistan | TJK | 2016 | 801.393840 |
| 2634 | Tajikistan | TJK | 2015 | 970.362600 |
| 2635 | Tajikistan | TJK | 2014 | 1094.430124 |
| 2636 | Tajikistan | TJK | 2013 | 1038.320717 |
| 2637 | Tajikistan | TJK | 2012 | 959.360218 |
| 2638 | Tajikistan | TJK | 2011 | 837.881495 |
| 2639 | Tajikistan | TJK | 2010 | 740.276191 |
| 2640 | Tanzania | TZA | 2020 | 1104.164429 |
| 2641 | Tanzania | TZA | 2019 | 1050.931763 |
| 2642 | Tanzania | TZA | 2018 | 1011.600159 |
| 2643 | Tanzania | TZA | 2017 | 975.904663 |
| 2644 | Tanzania | TZA | 2016 | 942.889038 |
| 2645 | Tanzania | TZA | 2015 | 929.799805 |
| 2646 | Tanzania | TZA | 2014 | 1013.428772 |
| 2647 | Tanzania | TZA | 2013 | 954.658813 |
| 2648 | Tanzania | TZA | 2012 | 854.540466 |
| 2649 | Tanzania | TZA | 2011 | 768.933411 |
| 2650 | Tanzania | TZA | 2010 | 730.782349 |
| 2651 | Thailand | THA | 2020 | 7001.785460 |
| 2652 | Thailand | THA | 2019 | 7628.576033 |
| 2653 | Thailand | THA | 2018 | 7124.558810 |
| 2654 | Thailand | THA | 2017 | 6436.789660 |
| 2655 | Thailand | THA | 2016 | 5854.463908 |
| 2656 | Thailand | THA | 2015 | 5708.794091 |
| 2657 | Thailand | THA | 2014 | 5822.377783 |
| 2658 | Thailand | THA | 2013 | 6041.133948 |
| 2659 | Thailand | THA | 2012 | 5748.632721 |
| 2660 | Thailand | THA | 2011 | 5396.643586 |
| 2661 | Thailand | THA | 2010 | 4996.372098 |
| 2662 | Timor-Leste | TLS | 2020 | 1663.559629 |
| 2663 | Timor-Leste | TLS | 2019 | 1583.078603 |
| 2664 | Timor-Leste | TLS | 2018 | 1241.164485 |
| 2665 | Timor-Leste | TLS | 2017 | 1285.523976 |
| 2666 | Timor-Leste | TLS | 2016 | 1349.546777 |
| 2667 | Timor-Leste | TLS | 2015 | 1322.929094 |
| 2668 | Timor-Leste | TLS | 2014 | 1221.723960 |
| 2669 | Timor-Leste | TLS | 2013 | 1201.602507 |
| 2670 | Timor-Leste | TLS | 2012 | 1020.110295 |
| 2671 | Timor-Leste | TLS | 2011 | 936.708968 |
| 2672 | Timor-Leste | TLS | 2010 | 810.216484 |
| 2673 | Togo | TGO | 2020 | 886.699512 |
| 2674 | Togo | TGO | 2019 | 848.304535 |
| 2675 | Togo | TGO | 2018 | 873.554887 |
| 2676 | Togo | TGO | 2017 | 813.395006 |
| 2677 | Togo | TGO | 2016 | 792.440551 |
| 2678 | Togo | TGO | 2015 | 770.143379 |
| 2679 | Togo | TGO | 2014 | 877.192473 |
| 2680 | Togo | TGO | 2013 | 847.387500 |
| 2681 | Togo | TGO | 2012 | 781.554340 |
| 2682 | Togo | TGO | 2011 | 803.482397 |
| 2683 | Togo | TGO | 2010 | 722.229400 |
| 2684 | Tonga | TON | 2020 | 4605.970841 |
| 2685 | Tonga | TON | 2019 | 4878.978686 |
| 2686 | Tonga | TON | 2018 | 4649.613301 |
| 2687 | Tonga | TON | 2017 | 4367.256603 |
| 2688 | Tonga | TON | 2016 | 3978.437686 |
| 2689 | Tonga | TON | 2015 | 4117.931047 |
| 2690 | Tonga | TON | 2014 | 4125.425454 |
| 2691 | Tonga | TON | 2013 | 4208.187891 |
| 2692 | Tonga | TON | 2012 | 4378.571528 |
| 2693 | Tonga | TON | 2011 | 3852.144462 |
| 2694 | Tonga | TON | 2010 | 3416.110699 |
| 2695 | Trinidad and Tobago | TTO | 2020 | 13705.900229 |
| 2696 | Trinidad and Tobago | TTO | 2019 | 15642.406719 |
| 2697 | Trinidad and Tobago | TTO | 2018 | 16328.126893 |
| 2698 | Trinidad and Tobago | TTO | 2017 | 16258.748929 |
| 2699 | Trinidad and Tobago | TTO | 2016 | 16139.105258 |
| 2700 | Trinidad and Tobago | TTO | 2015 | 18508.770503 |
| 2701 | Trinidad and Tobago | TTO | 2014 | 20473.404028 |
| 2702 | Trinidad and Tobago | TTO | 2013 | 19927.403905 |
| 2703 | Trinidad and Tobago | TTO | 2012 | 19110.053895 |
| 2704 | Trinidad and Tobago | TTO | 2011 | 17910.319154 |
| 2705 | Trinidad and Tobago | TTO | 2010 | 15711.558706 |
| 2706 | Tunisia | TUN | 2020 | 3497.719027 |
| 2707 | Tunisia | TUN | 2019 | 3477.836181 |
| 2708 | Tunisia | TUN | 2018 | 3577.175342 |
| 2709 | Tunisia | TUN | 2017 | 3569.718839 |
| 2710 | Tunisia | TUN | 2016 | 3796.109600 |
| 2711 | Tunisia | TUN | 2015 | 3960.924849 |
| 2712 | Tunisia | TUN | 2014 | 4398.638695 |
| 2713 | Tunisia | TUN | 2013 | 4308.338305 |
| 2714 | Tunisia | TUN | 2012 | 4233.916254 |
| 2715 | Tunisia | TUN | 2011 | 4361.949122 |
| 2716 | Tunisia | TUN | 2010 | 4241.011910 |
| 2717 | Turkiye | TUR | 2020 | 8638.739133 |
| 2718 | Turkiye | TUR | 2019 | 9215.440875 |
| 2719 | Turkiye | TUR | 2018 | 9568.836190 |
| 2720 | Turkiye | TUR | 2017 | 10695.550196 |
| 2721 | Turkiye | TUR | 2016 | 10970.045895 |
| 2722 | Turkiye | TUR | 2015 | 11049.995110 |
| 2723 | Turkiye | TUR | 2014 | 12165.220135 |
| 2724 | Turkiye | TUR | 2013 | 12578.187863 |
| 2725 | Turkiye | TUR | 2012 | 11713.284983 |
| 2726 | Turkiye | TUR | 2011 | 11300.785222 |
| 2727 | Turkiye | TUR | 2010 | 10622.702044 |
| 2728 | Turkmenistan | TKM | 2020 | 7330.366288 |
| 2729 | Turkmenistan | TKM | 2019 | 7344.880204 |
| 2730 | Turkmenistan | TKM | 2018 | 6721.349540 |
| 2731 | Turkmenistan | TKM | 2017 | 6354.532830 |
| 2732 | Turkmenistan | TKM | 2016 | 6163.253406 |
| 2733 | Turkmenistan | TKM | 2015 | 6208.296655 |
| 2734 | Turkmenistan | TKM | 2014 | 7685.509859 |
| 2735 | Turkmenistan | TKM | 2013 | 7049.797505 |
| 2736 | Turkmenistan | TKM | 2012 | 6441.886618 |
| 2737 | Turkmenistan | TKM | 2011 | 5453.155005 |
| 2738 | Turkmenistan | TKM | 2010 | 4286.880505 |
| 2739 | Turks and Caicos Islands | TCA | 2020 | 20882.261270 |
| 2740 | Turks and Caicos Islands | TCA | 2019 | 27795.148561 |
| 2741 | Turks and Caicos Islands | TCA | 2018 | 26831.971461 |
| 2742 | Turks and Caicos Islands | TCA | 2017 | 25659.195864 |
| 2743 | Turks and Caicos Islands | TCA | 2016 | 26995.032160 |
| 2744 | Turks and Caicos Islands | TCA | 2015 | 25783.294105 |
| 2745 | Turks and Caicos Islands | TCA | 2014 | 24040.874661 |
| 2746 | Turks and Caicos Islands | TCA | 2013 | 22451.568733 |
| 2747 | Turks and Caicos Islands | TCA | 2012 | 22666.406908 |
| 2748 | Turks and Caicos Islands | TCA | 2011 | 23649.714434 |
| 2749 | Turks and Caicos Islands | TCA | 2010 | 23103.942676 |
| 2750 | Tuvalu | TUV | 2020 | 4674.911403 |
| 2751 | Tuvalu | TUV | 2019 | 4940.050983 |
| 2752 | Tuvalu | TUV | 2018 | 4419.259998 |
| 2753 | Tuvalu | TUV | 2017 | 4181.436586 |
| 2754 | Tuvalu | TUV | 2016 | 3836.073003 |
| 2755 | Tuvalu | TUV | 2015 | 3384.383201 |
| 2756 | Tuvalu | TUV | 2014 | 3556.379728 |
| 2757 | Tuvalu | TUV | 2013 | 3536.901505 |
| 2758 | Tuvalu | TUV | 2012 | 3624.984289 |
| 2759 | Tuvalu | TUV | 2011 | 3663.267055 |
| 2760 | Tuvalu | TUV | 2010 | 3043.166680 |
| 2761 | Uganda | UGA | 2020 | 846.881199 |
| 2762 | Uganda | UGA | 2019 | 823.024733 |
| 2763 | Uganda | UGA | 2018 | 793.128082 |
| 2764 | Uganda | UGA | 2017 | 766.177604 |
| 2765 | Uganda | UGA | 2016 | 753.684406 |
| 2766 | Uganda | UGA | 2015 | 864.180059 |
| 2767 | Uganda | UGA | 2014 | 897.509729 |
| 2768 | Uganda | UGA | 2013 | 819.757867 |
| 2769 | Uganda | UGA | 2012 | 796.711139 |
| 2770 | Uganda | UGA | 2011 | 837.095884 |
| 2771 | Uganda | UGA | 2010 | 824.737671 |
| 2772 | Ukraine | UKR | 2020 | 3751.737305 |
| 2773 | Ukraine | UKR | 2019 | 3661.457764 |
| 2774 | Ukraine | UKR | 2018 | 3096.562500 |
| 2775 | Ukraine | UKR | 2017 | 2638.325439 |
| 2776 | Ukraine | UKR | 2016 | 2187.727539 |
| 2777 | Ukraine | UKR | 2015 | 2124.662598 |
| 2778 | Ukraine | UKR | 2014 | 3104.653809 |
| 2779 | Ukraine | UKR | 2013 | 4187.739746 |
| 2780 | Ukraine | UKR | 2012 | 4004.789795 |
| 2781 | Ukraine | UKR | 2011 | 3704.842285 |
| 2782 | Ukraine | UKR | 2010 | 3078.414795 |
| 2783 | United Arab Emirates | ARE | 2020 | 37629.174169 |
| 2784 | United Arab Emirates | ARE | 2019 | 45376.170838 |
| 2785 | United Arab Emirates | ARE | 2018 | 46722.268718 |
| 2786 | United Arab Emirates | ARE | 2017 | 43063.967477 |
| 2787 | United Arab Emirates | ARE | 2016 | 41054.539570 |
| 2788 | United Arab Emirates | ARE | 2015 | 41525.138903 |
| 2789 | United Arab Emirates | ARE | 2014 | 46865.964598 |
| 2790 | United Arab Emirates | ARE | 2013 | 45729.607676 |
| 2791 | United Arab Emirates | ARE | 2012 | 44386.786079 |
| 2792 | United Arab Emirates | ARE | 2011 | 42078.613813 |
| 2793 | United Arab Emirates | ARE | 2010 | 35392.260967 |
| 2794 | United Kingdom | GBR | 2020 | 40217.009012 |
| 2795 | United Kingdom | GBR | 2019 | 42662.535374 |
| 2796 | United Kingdom | GBR | 2018 | 43203.814106 |
| 2797 | United Kingdom | GBR | 2017 | 40572.121482 |
| 2798 | United Kingdom | GBR | 2016 | 40985.235138 |
| 2799 | United Kingdom | GBR | 2015 | 44964.391144 |
| 2800 | United Kingdom | GBR | 2014 | 47439.616590 |
| 2801 | United Kingdom | GBR | 2013 | 43426.298141 |
| 2802 | United Kingdom | GBR | 2012 | 42497.340497 |
| 2803 | United Kingdom | GBR | 2011 | 42109.641880 |
| 2804 | United Kingdom | GBR | 2010 | 39598.957120 |
| 2805 | United States | USA | 2020 | 63528.634303 |
| 2806 | United States | USA | 2019 | 65120.394663 |
| 2807 | United States | USA | 2018 | 62823.309438 |
| 2808 | United States | USA | 2017 | 59907.754261 |
| 2809 | United States | USA | 2016 | 57866.744934 |
| 2810 | United States | USA | 2015 | 56762.729452 |
| 2811 | United States | USA | 2014 | 55123.849787 |
| 2812 | United States | USA | 2013 | 53291.127689 |
| 2813 | United States | USA | 2012 | 51784.418574 |
| 2814 | United States | USA | 2011 | 50065.966504 |
| 2815 | United States | USA | 2010 | 48650.643128 |
| 2816 | Uruguay | URY | 2020 | 15650.499303 |
| 2817 | Uruguay | URY | 2019 | 18098.361549 |
| 2818 | Uruguay | URY | 2018 | 19026.049817 |
| 2819 | Uruguay | URY | 2017 | 18995.397020 |
| 2820 | Uruguay | URY | 2016 | 16837.940380 |
| 2821 | Uruguay | URY | 2015 | 16950.753169 |
| 2822 | Uruguay | URY | 2014 | 18131.578847 |
| 2823 | Uruguay | URY | 2013 | 18140.892213 |
| 2824 | Uruguay | URY | 2012 | 16087.252078 |
| 2825 | Uruguay | URY | 2011 | 14975.562819 |
| 2826 | Uruguay | URY | 2010 | 12512.594127 |
| 2827 | Uzbekistan | UZB | 2020 | 1759.307471 |
| 2828 | Uzbekistan | UZB | 2019 | 1795.201768 |
| 2829 | Uzbekistan | UZB | 2018 | 1604.258642 |
| 2830 | Uzbekistan | UZB | 2017 | 1916.764625 |
| 2831 | Uzbekistan | UZB | 2016 | 2704.677189 |
| 2832 | Uzbekistan | UZB | 2015 | 2753.971058 |
| 2833 | Uzbekistan | UZB | 2014 | 2628.460054 |
| 2834 | Uzbekistan | UZB | 2013 | 2419.718744 |
| 2835 | Uzbekistan | UZB | 2012 | 2267.623275 |
| 2836 | Uzbekistan | UZB | 2011 | 2051.129515 |
| 2837 | Uzbekistan | UZB | 2010 | 1742.349256 |
| 2838 | Vanuatu | VUT | 2020 | 2917.756849 |
| 2839 | Vanuatu | VUT | 2019 | 3076.589886 |
| 2840 | Vanuatu | VUT | 2018 | 3076.835315 |
| 2841 | Vanuatu | VUT | 2017 | 3032.197030 |
| 2842 | Vanuatu | VUT | 2016 | 2757.203306 |
| 2843 | Vanuatu | VUT | 2015 | 2643.886886 |
| 2844 | Vanuatu | VUT | 2014 | 2861.203154 |
| 2845 | Vanuatu | VUT | 2013 | 2877.444528 |
| 2846 | Vanuatu | VUT | 2012 | 2906.342461 |
| 2847 | Vanuatu | VUT | 2011 | 3064.751201 |
| 2848 | Vanuatu | VUT | 2010 | 2732.551567 |
| 2849 | Venezuela, RB | VEN | 2020 | NaN |
| 2850 | Venezuela, RB | VEN | 2019 | NaN |
| 2851 | Venezuela, RB | VEN | 2018 | NaN |
| 2852 | Venezuela, RB | VEN | 2017 | NaN |
| 2853 | Venezuela, RB | VEN | 2016 | NaN |
| 2854 | Venezuela, RB | VEN | 2015 | NaN |
| 2855 | Venezuela, RB | VEN | 2014 | 15975.729375 |
| 2856 | Venezuela, RB | VEN | 2013 | 12433.980785 |
| 2857 | Venezuela, RB | VEN | 2012 | 12937.927597 |
| 2858 | Venezuela, RB | VEN | 2011 | 10877.112364 |
| 2859 | Venezuela, RB | VEN | 2010 | 13692.914967 |
| 2860 | Viet Nam | VNM | 2020 | 3586.347176 |
| 2861 | Viet Nam | VNM | 2019 | 3491.091410 |
| 2862 | Viet Nam | VNM | 2018 | 3267.225069 |
| 2863 | Viet Nam | VNM | 2017 | 2992.071532 |
| 2864 | Viet Nam | VNM | 2016 | 2760.717101 |
| 2865 | Viet Nam | VNM | 2015 | 2595.234844 |
| 2866 | Viet Nam | VNM | 2014 | 2558.778758 |
| 2867 | Viet Nam | VNM | 2013 | 2367.499331 |
| 2868 | Viet Nam | VNM | 2012 | 2190.232440 |
| 2869 | Viet Nam | VNM | 2011 | 1953.557150 |
| 2870 | Viet Nam | VNM | 2010 | 1684.011772 |
| 2871 | Virgin Islands (U.S.) | VIR | 2020 | 39411.045254 |
| 2872 | Virgin Islands (U.S.) | VIR | 2019 | 38633.529892 |
| 2873 | Virgin Islands (U.S.) | VIR | 2018 | 36663.208755 |
| 2874 | Virgin Islands (U.S.) | VIR | 2017 | 35365.069304 |
| 2875 | Virgin Islands (U.S.) | VIR | 2016 | 35324.974887 |
| 2876 | Virgin Islands (U.S.) | VIR | 2015 | 34007.352941 |
| 2877 | Virgin Islands (U.S.) | VIR | 2014 | 33045.364380 |
| 2878 | Virgin Islands (U.S.) | VIR | 2013 | 34597.976694 |
| 2879 | Virgin Islands (U.S.) | VIR | 2012 | 37795.319259 |
| 2880 | Virgin Islands (U.S.) | VIR | 2011 | 38997.137316 |
| 2881 | Virgin Islands (U.S.) | VIR | 2010 | 39905.128418 |
| 2882 | West Bank and Gaza | PSE | 2020 | 3233.568638 |
| 2883 | West Bank and Gaza | PSE | 2019 | 3656.858271 |
| 2884 | West Bank and Gaza | PSE | 2018 | 3562.330943 |
| 2885 | West Bank and Gaza | PSE | 2017 | 3620.360487 |
| 2886 | West Bank and Gaza | PSE | 2016 | 3527.613824 |
| 2887 | West Bank and Gaza | PSE | 2015 | 3272.154324 |
| 2888 | West Bank and Gaza | PSE | 2014 | 3352.112595 |
| 2889 | West Bank and Gaza | PSE | 2013 | 3315.297539 |
| 2890 | West Bank and Gaza | PSE | 2012 | 3067.438727 |
| 2891 | West Bank and Gaza | PSE | 2011 | 2880.798437 |
| 2892 | West Bank and Gaza | PSE | 2010 | 2557.075624 |
| 2893 | Yemen, Rep. | YEM | 2020 | 578.512010 |
| 2894 | Yemen, Rep. | YEM | 2019 | 693.816504 |
| 2895 | Yemen, Rep. | YEM | 2018 | 701.714869 |
| 2896 | Yemen, Rep. | YEM | 2017 | 893.716494 |
| 2897 | Yemen, Rep. | YEM | 2016 | 1069.816998 |
| 2898 | Yemen, Rep. | YEM | 2015 | 1488.416269 |
| 2899 | Yemen, Rep. | YEM | 2014 | 1557.601406 |
| 2900 | Yemen, Rep. | YEM | 2013 | 1497.747941 |
| 2901 | Yemen, Rep. | YEM | 2012 | 1349.990610 |
| 2902 | Yemen, Rep. | YEM | 2011 | 1284.617635 |
| 2903 | Yemen, Rep. | YEM | 2010 | 1249.063085 |
| 2904 | Zambia | ZMB | 2020 | 956.831729 |
| 2905 | Zambia | ZMB | 2019 | 1268.120941 |
| 2906 | Zambia | ZMB | 2018 | 1475.199883 |
| 2907 | Zambia | ZMB | 2017 | 1495.752138 |
| 2908 | Zambia | ZMB | 2016 | 1249.923143 |
| 2909 | Zambia | ZMB | 2015 | 1307.909649 |
| 2910 | Zambia | ZMB | 2014 | 1724.576220 |
| 2911 | Zambia | ZMB | 2013 | 1840.320553 |
| 2912 | Zambia | ZMB | 2012 | 1729.647471 |
| 2913 | Zambia | ZMB | 2011 | 1644.456831 |
| 2914 | Zambia | ZMB | 2010 | 1469.361450 |
| 2915 | Zimbabwe | ZWE | 2020 | 1372.696674 |
| 2916 | Zimbabwe | ZWE | 2019 | 1421.868596 |
| 2917 | Zimbabwe | ZWE | 2018 | 2269.177012 |
| 2918 | Zimbabwe | ZWE | 2017 | 1192.107012 |
| 2919 | Zimbabwe | ZWE | 2016 | 1421.787791 |
| 2920 | Zimbabwe | ZWE | 2015 | 1410.329173 |
| 2921 | Zimbabwe | ZWE | 2014 | 1407.034291 |
| 2922 | Zimbabwe | ZWE | 2013 | 1408.367810 |
| 2923 | Zimbabwe | ZWE | 2012 | 1290.193957 |
| 2924 | Zimbabwe | ZWE | 2011 | 1082.615773 |
| 2925 | Zimbabwe | ZWE | 2010 | 937.840340 |
worldbank_gdp = pd.DataFrame(worldbank_gdp)
excel_worldbank_gdp = "worldbank_gdp.xlsx"
worldbank_gdp.to_excel(excel_worldbank_gdp, index=False)
indicator = 'AG.LND.FRST.K2?date=2010:2020'
url = "http://api.worldbank.org/v2/countries/all/indicators/%s&format=json&per_page=5000" % indicator
response = requests.get(url)
result = response.content
result = json.loads(result)
worldbank_forest = pd.DataFrame.from_dict(result[1])
worldbank_forest ['country'] = worldbank_forest [['country']].applymap(lambda x : x['value'])
worldbank_forest.country.unique()
worldbank_forest = worldbank_forest[['country', 'countryiso3code', 'date', 'value']]
worldbank_forest.columns = ['Country_name', 'countrycode', 'year', 'ForestArea']
worldbank_forest
| Country_name | countrycode | year | ForestArea | |
|---|---|---|---|---|
| 0 | Africa Eastern and Southern | AFE | 2020 | 4.479395e+06 |
| 1 | Africa Eastern and Southern | AFE | 2019 | 4.511676e+06 |
| 2 | Africa Eastern and Southern | AFE | 2018 | 4.544315e+06 |
| 3 | Africa Eastern and Southern | AFE | 2017 | 4.575901e+06 |
| 4 | Africa Eastern and Southern | AFE | 2016 | 4.607876e+06 |
| 5 | Africa Eastern and Southern | AFE | 2015 | 4.640642e+06 |
| 6 | Africa Eastern and Southern | AFE | 2014 | 4.671832e+06 |
| 7 | Africa Eastern and Southern | AFE | 2013 | 4.703022e+06 |
| 8 | Africa Eastern and Southern | AFE | 2012 | 4.734211e+06 |
| 9 | Africa Eastern and Southern | AFE | 2011 | 4.765401e+06 |
| 10 | Africa Eastern and Southern | AFE | 2010 | 4.796591e+06 |
| 11 | Africa Western and Central | AFW | 2020 | 1.792581e+06 |
| 12 | Africa Western and Central | AFW | 2019 | 1.800220e+06 |
| 13 | Africa Western and Central | AFW | 2018 | 1.807899e+06 |
| 14 | Africa Western and Central | AFW | 2017 | 1.815608e+06 |
| 15 | Africa Western and Central | AFW | 2016 | 1.822961e+06 |
| 16 | Africa Western and Central | AFW | 2015 | 1.830344e+06 |
| 17 | Africa Western and Central | AFW | 2014 | 1.838300e+06 |
| 18 | Africa Western and Central | AFW | 2013 | 1.846257e+06 |
| 19 | Africa Western and Central | AFW | 2012 | 1.854213e+06 |
| 20 | Africa Western and Central | AFW | 2011 | 1.862169e+06 |
| 21 | Africa Western and Central | AFW | 2010 | 1.870126e+06 |
| 22 | Arab World | ARB | 2020 | 3.679807e+05 |
| 23 | Arab World | ARB | 2019 | 3.703027e+05 |
| 24 | Arab World | ARB | 2018 | 3.726341e+05 |
| 25 | Arab World | ARB | 2017 | 3.751917e+05 |
| 26 | Arab World | ARB | 2016 | 3.777306e+05 |
| 27 | Arab World | ARB | 2015 | 3.800382e+05 |
| 28 | Arab World | ARB | 2014 | 3.824634e+05 |
| 29 | Arab World | ARB | 2013 | 3.848885e+05 |
| 30 | Arab World | ARB | 2012 | 3.873137e+05 |
| 31 | Arab World | ARB | 2011 | 4.613088e+05 |
| 32 | Arab World | ARB | 2010 | 4.637340e+05 |
| 33 | Caribbean small states | CSS | 2020 | 3.636392e+05 |
| 34 | Caribbean small states | CSS | 2019 | 3.639311e+05 |
| 35 | Caribbean small states | CSS | 2018 | 3.642234e+05 |
| 36 | Caribbean small states | CSS | 2017 | 3.645153e+05 |
| 37 | Caribbean small states | CSS | 2016 | 3.647579e+05 |
| 38 | Caribbean small states | CSS | 2015 | 3.650410e+05 |
| 39 | Caribbean small states | CSS | 2014 | 3.653383e+05 |
| 40 | Caribbean small states | CSS | 2013 | 3.656356e+05 |
| 41 | Caribbean small states | CSS | 2012 | 3.659328e+05 |
| 42 | Caribbean small states | CSS | 2011 | 3.662301e+05 |
| 43 | Caribbean small states | CSS | 2010 | 3.665274e+05 |
| 44 | Central Europe and the Baltics | CEB | 2020 | 3.818818e+05 |
| 45 | Central Europe and the Baltics | CEB | 2019 | 3.815749e+05 |
| 46 | Central Europe and the Baltics | CEB | 2018 | 3.812580e+05 |
| 47 | Central Europe and the Baltics | CEB | 2017 | 3.809400e+05 |
| 48 | Central Europe and the Baltics | CEB | 2016 | 3.803365e+05 |
| 49 | Central Europe and the Baltics | CEB | 2015 | 3.797437e+05 |
| 50 | Central Europe and the Baltics | CEB | 2014 | 3.782906e+05 |
| 51 | Central Europe and the Baltics | CEB | 2013 | 3.768375e+05 |
| 52 | Central Europe and the Baltics | CEB | 2012 | 3.753844e+05 |
| 53 | Central Europe and the Baltics | CEB | 2011 | 3.739313e+05 |
| 54 | Central Europe and the Baltics | CEB | 2010 | 3.724782e+05 |
| 55 | Early-demographic dividend | EAR | 2020 | 7.589318e+06 |
| 56 | Early-demographic dividend | EAR | 2019 | 7.610957e+06 |
| 57 | Early-demographic dividend | EAR | 2018 | 7.632988e+06 |
| 58 | Early-demographic dividend | EAR | 2017 | 7.655531e+06 |
| 59 | Early-demographic dividend | EAR | 2016 | 7.686805e+06 |
| 60 | Early-demographic dividend | EAR | 2015 | 7.702173e+06 |
| 61 | Early-demographic dividend | EAR | 2014 | 7.732699e+06 |
| 62 | Early-demographic dividend | EAR | 2013 | 7.763226e+06 |
| 63 | Early-demographic dividend | EAR | 2012 | 7.793753e+06 |
| 64 | Early-demographic dividend | EAR | 2011 | 7.824280e+06 |
| 65 | Early-demographic dividend | EAR | 2010 | 7.854807e+06 |
| 66 | East Asia & Pacific | EAS | 2020 | 6.640831e+06 |
| 67 | East Asia & Pacific | EAS | 2019 | 6.632993e+06 |
| 68 | East Asia & Pacific | EAS | 2018 | 6.625322e+06 |
| 69 | East Asia & Pacific | EAS | 2017 | 6.617837e+06 |
| 70 | East Asia & Pacific | EAS | 2016 | 6.617999e+06 |
| 71 | East Asia & Pacific | EAS | 2015 | 6.588415e+06 |
| 72 | East Asia & Pacific | EAS | 2014 | 6.575875e+06 |
| 73 | East Asia & Pacific | EAS | 2013 | 6.563336e+06 |
| 74 | East Asia & Pacific | EAS | 2012 | 6.550796e+06 |
| 75 | East Asia & Pacific | EAS | 2011 | 6.538257e+06 |
| 76 | East Asia & Pacific | EAS | 2010 | 6.525717e+06 |
| 77 | East Asia & Pacific (excluding high income) | EAP | 2020 | 4.875109e+06 |
| 78 | East Asia & Pacific (excluding high income) | EAP | 2019 | 4.867438e+06 |
| 79 | East Asia & Pacific (excluding high income) | EAP | 2018 | 4.859767e+06 |
| 80 | East Asia & Pacific (excluding high income) | EAP | 2017 | 4.852100e+06 |
| 81 | East Asia & Pacific (excluding high income) | EAP | 2016 | 4.851972e+06 |
| 82 | East Asia & Pacific (excluding high income) | EAP | 2015 | 4.831631e+06 |
| 83 | East Asia & Pacific (excluding high income) | EAP | 2014 | 4.826038e+06 |
| 84 | East Asia & Pacific (excluding high income) | EAP | 2013 | 4.820445e+06 |
| 85 | East Asia & Pacific (excluding high income) | EAP | 2012 | 4.814852e+06 |
| 86 | East Asia & Pacific (excluding high income) | EAP | 2011 | 4.809259e+06 |
| 87 | East Asia & Pacific (excluding high income) | EAP | 2010 | 4.803665e+06 |
| 88 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2020 | 4.814808e+06 |
| 89 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2019 | 4.806925e+06 |
| 90 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2018 | 4.799042e+06 |
| 91 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2017 | 4.791162e+06 |
| 92 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2016 | 4.790822e+06 |
| 93 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2015 | 4.770269e+06 |
| 94 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2014 | 4.764463e+06 |
| 95 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2013 | 4.758658e+06 |
| 96 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2012 | 4.752852e+06 |
| 97 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2011 | 4.747047e+06 |
| 98 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2010 | 4.741242e+06 |
| 99 | Euro area | EMU | 2020 | 1.036487e+06 |
| 100 | Euro area | EMU | 2019 | 1.034958e+06 |
| 101 | Euro area | EMU | 2018 | 1.033420e+06 |
| 102 | Euro area | EMU | 2017 | 1.031881e+06 |
| 103 | Euro area | EMU | 2016 | 1.030071e+06 |
| 104 | Euro area | EMU | 2015 | 1.028470e+06 |
| 105 | Euro area | EMU | 2014 | 1.026274e+06 |
| 106 | Euro area | EMU | 2013 | 1.024078e+06 |
| 107 | Euro area | EMU | 2012 | 1.021882e+06 |
| 108 | Euro area | EMU | 2011 | 1.019686e+06 |
| 109 | Euro area | EMU | 2010 | 1.017491e+06 |
| 110 | Europe & Central Asia | ECS | 2020 | 1.057147e+07 |
| 111 | Europe & Central Asia | ECS | 2019 | 1.056683e+07 |
| 112 | Europe & Central Asia | ECS | 2018 | 1.056217e+07 |
| 113 | Europe & Central Asia | ECS | 2017 | 1.055751e+07 |
| 114 | Europe & Central Asia | ECS | 2016 | 1.055104e+07 |
| 115 | Europe & Central Asia | ECS | 2015 | 1.054498e+07 |
| 116 | Europe & Central Asia | ECS | 2014 | 1.053923e+07 |
| 117 | Europe & Central Asia | ECS | 2013 | 1.053347e+07 |
| 118 | Europe & Central Asia | ECS | 2012 | 1.052772e+07 |
| 119 | Europe & Central Asia | ECS | 2011 | 1.052197e+07 |
| 120 | Europe & Central Asia | ECS | 2010 | 1.051622e+07 |
| 121 | Europe & Central Asia (excluding high income) | ECA | 2020 | 8.850902e+06 |
| 122 | Europe & Central Asia (excluding high income) | ECA | 2019 | 8.848146e+06 |
| 123 | Europe & Central Asia (excluding high income) | ECA | 2018 | 8.845392e+06 |
| 124 | Europe & Central Asia (excluding high income) | ECA | 2017 | 8.842641e+06 |
| 125 | Europe & Central Asia (excluding high income) | ECA | 2016 | 8.838352e+06 |
| 126 | Europe & Central Asia (excluding high income) | ECA | 2015 | 8.834496e+06 |
| 127 | Europe & Central Asia (excluding high income) | ECA | 2014 | 8.832151e+06 |
| 128 | Europe & Central Asia (excluding high income) | ECA | 2013 | 8.829806e+06 |
| 129 | Europe & Central Asia (excluding high income) | ECA | 2012 | 8.827462e+06 |
| 130 | Europe & Central Asia (excluding high income) | ECA | 2011 | 8.825117e+06 |
| 131 | Europe & Central Asia (excluding high income) | ECA | 2010 | 8.822773e+06 |
| 132 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2020 | 9.034413e+06 |
| 133 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2019 | 9.031513e+06 |
| 134 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2018 | 9.028614e+06 |
| 135 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2017 | 9.025717e+06 |
| 136 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2016 | 9.021234e+06 |
| 137 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2015 | 9.016925e+06 |
| 138 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2014 | 9.013623e+06 |
| 139 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2013 | 9.010320e+06 |
| 140 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2012 | 9.007018e+06 |
| 141 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2011 | 9.003715e+06 |
| 142 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2010 | 9.000413e+06 |
| 143 | European Union | EUU | 2020 | 1.592314e+06 |
| 144 | European Union | EUU | 2019 | 1.590498e+06 |
| 145 | European Union | EUU | 2018 | 1.588671e+06 |
| 146 | European Union | EUU | 2017 | 1.586843e+06 |
| 147 | European Union | EUU | 2016 | 1.584695e+06 |
| 148 | European Union | EUU | 2015 | 1.582569e+06 |
| 149 | European Union | EUU | 2014 | 1.579282e+06 |
| 150 | European Union | EUU | 2013 | 1.575994e+06 |
| 151 | European Union | EUU | 2012 | 1.572707e+06 |
| 152 | European Union | EUU | 2011 | 1.569420e+06 |
| 153 | European Union | EUU | 2010 | 1.566133e+06 |
| 154 | Fragile and conflict affected situations | FCS | 2020 | 4.710928e+06 |
| 155 | Fragile and conflict affected situations | FCS | 2019 | 4.735958e+06 |
| 156 | Fragile and conflict affected situations | FCS | 2018 | 4.761632e+06 |
| 157 | Fragile and conflict affected situations | FCS | 2017 | 4.786820e+06 |
| 158 | Fragile and conflict affected situations | FCS | 2016 | 4.812630e+06 |
| 159 | Fragile and conflict affected situations | FCS | 2015 | 4.839527e+06 |
| 160 | Fragile and conflict affected situations | FCS | 2014 | 4.865396e+06 |
| 161 | Fragile and conflict affected situations | FCS | 2013 | 4.891265e+06 |
| 162 | Fragile and conflict affected situations | FCS | 2012 | 4.917134e+06 |
| 163 | Fragile and conflict affected situations | FCS | 2011 | 4.943003e+06 |
| 164 | Fragile and conflict affected situations | FCS | 2010 | 4.968873e+06 |
| 165 | Heavily indebted poor countries (HIPC) | HPC | 2020 | 5.257492e+06 |
| 166 | Heavily indebted poor countries (HIPC) | HPC | 2019 | 5.290657e+06 |
| 167 | Heavily indebted poor countries (HIPC) | HPC | 2018 | 5.324413e+06 |
| 168 | Heavily indebted poor countries (HIPC) | HPC | 2017 | 5.357639e+06 |
| 169 | Heavily indebted poor countries (HIPC) | HPC | 2016 | 5.391094e+06 |
| 170 | Heavily indebted poor countries (HIPC) | HPC | 2015 | 5.425547e+06 |
| 171 | Heavily indebted poor countries (HIPC) | HPC | 2014 | 5.457466e+06 |
| 172 | Heavily indebted poor countries (HIPC) | HPC | 2013 | 5.489385e+06 |
| 173 | Heavily indebted poor countries (HIPC) | HPC | 2012 | 5.521305e+06 |
| 174 | Heavily indebted poor countries (HIPC) | HPC | 2011 | 5.624794e+06 |
| 175 | Heavily indebted poor countries (HIPC) | HPC | 2010 | 5.656713e+06 |
| 176 | High income | 2020 | 1.051011e+07 | |
| 177 | High income | 2019 | 1.050719e+07 | |
| 178 | High income | 2018 | 1.050442e+07 | |
| 179 | High income | 2017 | 1.050183e+07 | |
| 180 | High income | 2016 | 1.050207e+07 | |
| 181 | High income | 2015 | 1.048998e+07 | |
| 182 | High income | 2014 | 1.047537e+07 | |
| 183 | High income | 2013 | 1.046077e+07 | |
| 184 | High income | 2012 | 1.044617e+07 | |
| 185 | High income | 2011 | 1.043157e+07 | |
| 186 | High income | 2010 | 1.041695e+07 | |
| 187 | IBRD only | IBD | 2020 | 2.408976e+07 |
| 188 | IBRD only | IBD | 2019 | 2.410187e+07 |
| 189 | IBRD only | IBD | 2018 | 2.411510e+07 |
| 190 | IBRD only | IBD | 2017 | 2.412671e+07 |
| 191 | IBRD only | IBD | 2016 | 2.415563e+07 |
| 192 | IBRD only | IBD | 2015 | 2.416013e+07 |
| 193 | IBRD only | IBD | 2014 | 2.417824e+07 |
| 194 | IBRD only | IBD | 2013 | 2.419636e+07 |
| 195 | IBRD only | IBD | 2012 | 2.421447e+07 |
| 196 | IBRD only | IBD | 2011 | 2.423258e+07 |
| 197 | IBRD only | IBD | 2010 | 2.425070e+07 |
| 198 | IDA & IBRD total | IBT | 2020 | 3.051179e+07 |
| 199 | IDA & IBRD total | IBT | 2019 | 3.056222e+07 |
| 200 | IDA & IBRD total | IBT | 2018 | 3.061417e+07 |
| 201 | IDA & IBRD total | IBT | 2017 | 3.066349e+07 |
| 202 | IDA & IBRD total | IBT | 2016 | 3.073006e+07 |
| 203 | IDA & IBRD total | IBT | 2015 | 3.077338e+07 |
| 204 | IDA & IBRD total | IBT | 2014 | 3.083031e+07 |
| 205 | IDA & IBRD total | IBT | 2013 | 3.088723e+07 |
| 206 | IDA & IBRD total | IBT | 2012 | 3.094416e+07 |
| 207 | IDA & IBRD total | IBT | 2011 | 3.100108e+07 |
| 208 | IDA & IBRD total | IBT | 2010 | 3.105800e+07 |
| 209 | IDA blend | IDB | 2020 | 1.304621e+06 |
| 210 | IDA blend | IDB | 2019 | 1.307860e+06 |
| 211 | IDA blend | IDB | 2018 | 1.311098e+06 |
| 212 | IDA blend | IDB | 2017 | 1.314043e+06 |
| 213 | IDA blend | IDB | 2016 | 1.316723e+06 |
| 214 | IDA blend | IDB | 2015 | 1.319765e+06 |
| 215 | IDA blend | IDB | 2014 | 1.322903e+06 |
| 216 | IDA blend | IDB | 2013 | 1.326040e+06 |
| 217 | IDA blend | IDB | 2012 | 1.329177e+06 |
| 218 | IDA blend | IDB | 2011 | 1.332315e+06 |
| 219 | IDA blend | IDB | 2010 | 1.335452e+06 |
| 220 | IDA only | IDX | 2020 | 5.117406e+06 |
| 221 | IDA only | IDX | 2019 | 5.152490e+06 |
| 222 | IDA only | IDX | 2018 | 5.187971e+06 |
| 223 | IDA only | IDX | 2017 | 5.222736e+06 |
| 224 | IDA only | IDX | 2016 | 5.257706e+06 |
| 225 | IDA only | IDX | 2015 | 5.293491e+06 |
| 226 | IDA only | IDX | 2014 | 5.329163e+06 |
| 227 | IDA only | IDX | 2013 | 5.364836e+06 |
| 228 | IDA only | IDX | 2012 | 5.400508e+06 |
| 229 | IDA only | IDX | 2011 | 5.436180e+06 |
| 230 | IDA only | IDX | 2010 | 5.471853e+06 |
| 231 | IDA total | IDA | 2020 | 6.422027e+06 |
| 232 | IDA total | IDA | 2019 | 6.460349e+06 |
| 233 | IDA total | IDA | 2018 | 6.499068e+06 |
| 234 | IDA total | IDA | 2017 | 6.536780e+06 |
| 235 | IDA total | IDA | 2016 | 6.574428e+06 |
| 236 | IDA total | IDA | 2015 | 6.613256e+06 |
| 237 | IDA total | IDA | 2014 | 6.652066e+06 |
| 238 | IDA total | IDA | 2013 | 6.690876e+06 |
| 239 | IDA total | IDA | 2012 | 6.729686e+06 |
| 240 | IDA total | IDA | 2011 | 6.768495e+06 |
| 241 | IDA total | IDA | 2010 | 6.807305e+06 |
| 242 | Late-demographic dividend | LTE | 2020 | 1.760085e+07 |
| 243 | Late-demographic dividend | LTE | 2019 | 1.759365e+07 |
| 244 | Late-demographic dividend | LTE | 2018 | 1.758720e+07 |
| 245 | Late-demographic dividend | LTE | 2017 | 1.757862e+07 |
| 246 | Late-demographic dividend | LTE | 2016 | 1.757812e+07 |
| 247 | Late-demographic dividend | LTE | 2015 | 1.757041e+07 |
| 248 | Late-demographic dividend | LTE | 2014 | 1.756174e+07 |
| 249 | Late-demographic dividend | LTE | 2013 | 1.755307e+07 |
| 250 | Late-demographic dividend | LTE | 2012 | 1.754441e+07 |
| 251 | Late-demographic dividend | LTE | 2011 | 1.753574e+07 |
| 252 | Late-demographic dividend | LTE | 2010 | 1.752707e+07 |
| 253 | Latin America & Caribbean | LCN | 2020 | 9.320331e+06 |
| 254 | Latin America & Caribbean | LCN | 2019 | 9.344164e+06 |
| 255 | Latin America & Caribbean | LCN | 2018 | 9.369199e+06 |
| 256 | Latin America & Caribbean | LCN | 2017 | 9.392385e+06 |
| 257 | Latin America & Caribbean | LCN | 2016 | 9.426995e+06 |
| 258 | Latin America & Caribbean | LCN | 2015 | 9.456704e+06 |
| 259 | Latin America & Caribbean | LCN | 2014 | 9.485625e+06 |
| 260 | Latin America & Caribbean | LCN | 2013 | 9.514546e+06 |
| 261 | Latin America & Caribbean | LCN | 2012 | 9.543467e+06 |
| 262 | Latin America & Caribbean | LCN | 2011 | 9.572388e+06 |
| 263 | Latin America & Caribbean | LCN | 2010 | 9.601293e+06 |
| 264 | Latin America & Caribbean (excluding high income) | LAC | 2020 | 8.416227e+06 |
| 265 | Latin America & Caribbean (excluding high income) | LAC | 2019 | 8.440883e+06 |
| 266 | Latin America & Caribbean (excluding high income) | LAC | 2018 | 8.466494e+06 |
| 267 | Latin America & Caribbean (excluding high income) | LAC | 2017 | 8.490012e+06 |
| 268 | Latin America & Caribbean (excluding high income) | LAC | 2016 | 8.524705e+06 |
| 269 | Latin America & Caribbean (excluding high income) | LAC | 2015 | 8.554312e+06 |
| 270 | Latin America & Caribbean (excluding high income) | LAC | 2014 | 8.583478e+06 |
| 271 | Latin America & Caribbean (excluding high income) | LAC | 2013 | 8.612644e+06 |
| 272 | Latin America & Caribbean (excluding high income) | LAC | 2012 | 8.641811e+06 |
| 273 | Latin America & Caribbean (excluding high income) | LAC | 2011 | 8.670977e+06 |
| 274 | Latin America & Caribbean (excluding high income) | LAC | 2010 | 8.700144e+06 |
| 275 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2020 | 9.277298e+06 |
| 276 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2019 | 9.301136e+06 |
| 277 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2018 | 9.326177e+06 |
| 278 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2017 | 9.349371e+06 |
| 279 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2016 | 9.383997e+06 |
| 280 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2015 | 9.414282e+06 |
| 281 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2014 | 9.443714e+06 |
| 282 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2013 | 9.473145e+06 |
| 283 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2012 | 9.502577e+06 |
| 284 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2011 | 9.532008e+06 |
| 285 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2010 | 9.561439e+06 |
| 286 | Least developed countries: UN classification | LDC | 2020 | 5.352026e+06 |
| 287 | Least developed countries: UN classification | LDC | 2019 | 5.390473e+06 |
| 288 | Least developed countries: UN classification | LDC | 2018 | 5.429317e+06 |
| 289 | Least developed countries: UN classification | LDC | 2017 | 5.467439e+06 |
| 290 | Least developed countries: UN classification | LDC | 2016 | 5.505965e+06 |
| 291 | Least developed countries: UN classification | LDC | 2015 | 5.545313e+06 |
| 292 | Least developed countries: UN classification | LDC | 2014 | 5.584568e+06 |
| 293 | Least developed countries: UN classification | LDC | 2013 | 5.623823e+06 |
| 294 | Least developed countries: UN classification | LDC | 2012 | 5.663079e+06 |
| 295 | Least developed countries: UN classification | LDC | 2011 | 5.702334e+06 |
| 296 | Least developed countries: UN classification | LDC | 2010 | 5.741590e+06 |
| 297 | Low & middle income | LMY | 2020 | 2.952727e+07 |
| 298 | Low & middle income | LMY | 2019 | 2.957887e+07 |
| 299 | Low & middle income | LMY | 2018 | 2.963176e+07 |
| 300 | Low & middle income | LMY | 2017 | 2.968176e+07 |
| 301 | Low & middle income | LMY | 2016 | 2.974880e+07 |
| 302 | Low & middle income | LMY | 2015 | 2.979211e+07 |
| 303 | Low & middle income | LMY | 2014 | 2.984994e+07 |
| 304 | Low & middle income | LMY | 2013 | 2.990777e+07 |
| 305 | Low & middle income | LMY | 2012 | 2.996560e+07 |
| 306 | Low & middle income | LMY | 2011 | 3.002343e+07 |
| 307 | Low & middle income | LMY | 2010 | 3.008125e+07 |
| 308 | Low income | 2020 | 2.991863e+06 | |
| 309 | Low income | 2019 | 3.012204e+06 | |
| 310 | Low income | 2018 | 3.032941e+06 | |
| 311 | Low income | 2017 | 3.052952e+06 | |
| 312 | Low income | 2016 | 3.073376e+06 | |
| 313 | Low income | 2015 | 3.094616e+06 | |
| 314 | Low income | 2014 | 3.114777e+06 | |
| 315 | Low income | 2013 | 3.134938e+06 | |
| 316 | Low income | 2012 | 3.155099e+06 | |
| 317 | Low income | 2011 | 3.175259e+06 | |
| 318 | Low income | 2010 | 3.195420e+06 | |
| 319 | Lower middle income | 2020 | 5.845811e+06 | |
| 320 | Lower middle income | 2019 | 5.867388e+06 | |
| 321 | Lower middle income | 2018 | 5.889089e+06 | |
| 322 | Lower middle income | 2017 | 5.910918e+06 | |
| 323 | Lower middle income | 2016 | 5.932910e+06 | |
| 324 | Lower middle income | 2015 | 5.952520e+06 | |
| 325 | Lower middle income | 2014 | 5.974337e+06 | |
| 326 | Lower middle income | 2013 | 5.996153e+06 | |
| 327 | Lower middle income | 2012 | 6.017970e+06 | |
| 328 | Lower middle income | 2011 | 6.039787e+06 | |
| 329 | Lower middle income | 2010 | 6.061604e+06 | |
| 330 | Middle East & North Africa | MEA | 2020 | 2.300513e+05 |
| 331 | Middle East & North Africa | MEA | 2019 | 2.297408e+05 |
| 332 | Middle East & North Africa | MEA | 2018 | 2.293603e+05 |
| 333 | Middle East & North Africa | MEA | 2017 | 2.292047e+05 |
| 334 | Middle East & North Africa | MEA | 2016 | 2.291106e+05 |
| 335 | Middle East & North Africa | MEA | 2015 | 2.291232e+05 |
| 336 | Middle East & North Africa | MEA | 2014 | 2.289576e+05 |
| 337 | Middle East & North Africa | MEA | 2013 | 2.287920e+05 |
| 338 | Middle East & North Africa | MEA | 2012 | 2.286264e+05 |
| 339 | Middle East & North Africa | MEA | 2011 | 2.284608e+05 |
| 340 | Middle East & North Africa | MEA | 2010 | 2.282952e+05 |
| 341 | Middle East & North Africa (excluding high inc... | MNA | 2020 | 2.156092e+05 |
| 342 | Middle East & North Africa (excluding high inc... | MNA | 2019 | 2.152989e+05 |
| 343 | Middle East & North Africa (excluding high inc... | MNA | 2018 | 2.149176e+05 |
| 344 | Middle East & North Africa (excluding high inc... | MNA | 2017 | 2.147616e+05 |
| 345 | Middle East & North Africa (excluding high inc... | MNA | 2016 | 2.146671e+05 |
| 346 | Middle East & North Africa (excluding high inc... | MNA | 2015 | 2.144282e+05 |
| 347 | Middle East & North Africa (excluding high inc... | MNA | 2014 | 2.142848e+05 |
| 348 | Middle East & North Africa (excluding high inc... | MNA | 2013 | 2.141413e+05 |
| 349 | Middle East & North Africa (excluding high inc... | MNA | 2012 | 2.139979e+05 |
| 350 | Middle East & North Africa (excluding high inc... | MNA | 2011 | 2.138544e+05 |
| 351 | Middle East & North Africa (excluding high inc... | MNA | 2010 | 2.137110e+05 |
| 352 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2020 | 2.155078e+05 |
| 353 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2019 | 2.151975e+05 |
| 354 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2018 | 2.148162e+05 |
| 355 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2017 | 2.146602e+05 |
| 356 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2016 | 2.145657e+05 |
| 357 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2015 | 2.143268e+05 |
| 358 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2014 | 2.141837e+05 |
| 359 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2013 | 2.140407e+05 |
| 360 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2012 | 2.138976e+05 |
| 361 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2011 | 2.137546e+05 |
| 362 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2010 | 2.136115e+05 |
| 363 | Middle income | MIC | 2020 | 2.653541e+07 |
| 364 | Middle income | MIC | 2019 | 2.656667e+07 |
| 365 | Middle income | MIC | 2018 | 2.659882e+07 |
| 366 | Middle income | MIC | 2017 | 2.662880e+07 |
| 367 | Middle income | MIC | 2016 | 2.667542e+07 |
| 368 | Middle income | MIC | 2015 | 2.669749e+07 |
| 369 | Middle income | MIC | 2014 | 2.673516e+07 |
| 370 | Middle income | MIC | 2013 | 2.677283e+07 |
| 371 | Middle income | MIC | 2012 | 2.681050e+07 |
| 372 | Middle income | MIC | 2011 | 2.684817e+07 |
| 373 | Middle income | MIC | 2010 | 2.688583e+07 |
| 374 | North America | NAC | 2020 | 6.567241e+06 |
| 375 | North America | NAC | 2019 | 6.567611e+06 |
| 376 | North America | NAC | 2018 | 6.567981e+06 |
| 377 | North America | NAC | 2017 | 6.568350e+06 |
| 378 | North America | NAC | 2016 | 6.571720e+06 |
| 379 | North America | NAC | 2015 | 6.572117e+06 |
| 380 | North America | NAC | 2014 | 6.569780e+06 |
| 381 | North America | NAC | 2013 | 6.567443e+06 |
| 382 | North America | NAC | 2012 | 6.565106e+06 |
| 383 | North America | NAC | 2011 | 6.562769e+06 |
| 384 | North America | NAC | 2010 | 6.560432e+06 |
| 385 | Not classified | 2020 | NaN | |
| 386 | Not classified | 2019 | NaN | |
| 387 | Not classified | 2018 | NaN | |
| 388 | Not classified | 2017 | NaN | |
| 389 | Not classified | 2016 | NaN | |
| 390 | Not classified | 2015 | NaN | |
| 391 | Not classified | 2014 | NaN | |
| 392 | Not classified | 2013 | NaN | |
| 393 | Not classified | 2012 | NaN | |
| 394 | Not classified | 2011 | NaN | |
| 395 | Not classified | 2010 | NaN | |
| 396 | OECD members | OED | 2020 | 1.163270e+07 |
| 397 | OECD members | OED | 2019 | 1.163136e+07 |
| 398 | OECD members | OED | 2018 | 1.163016e+07 |
| 399 | OECD members | OED | 2017 | 1.162915e+07 |
| 400 | OECD members | OED | 2016 | 1.163156e+07 |
| 401 | OECD members | OED | 2015 | 1.162267e+07 |
| 402 | OECD members | OED | 2014 | 1.161030e+07 |
| 403 | OECD members | OED | 2013 | 1.159793e+07 |
| 404 | OECD members | OED | 2012 | 1.158556e+07 |
| 405 | OECD members | OED | 2011 | 1.157319e+07 |
| 406 | OECD members | OED | 2010 | 1.156083e+07 |
| 407 | Other small states | OSS | 2020 | 5.835463e+05 |
| 408 | Other small states | OSS | 2019 | 5.857652e+05 |
| 409 | Other small states | OSS | 2018 | 5.879847e+05 |
| 410 | Other small states | OSS | 2017 | 5.902068e+05 |
| 411 | Other small states | OSS | 2016 | 5.922479e+05 |
| 412 | Other small states | OSS | 2015 | 5.944680e+05 |
| 413 | Other small states | OSS | 2014 | 5.965182e+05 |
| 414 | Other small states | OSS | 2013 | 5.985684e+05 |
| 415 | Other small states | OSS | 2012 | 6.006187e+05 |
| 416 | Other small states | OSS | 2011 | 6.026689e+05 |
| 417 | Other small states | OSS | 2010 | 6.047191e+05 |
| 418 | Pacific island small states | PSS | 2020 | 4.393320e+04 |
| 419 | Pacific island small states | PSS | 2019 | 4.387740e+04 |
| 420 | Pacific island small states | PSS | 2018 | 4.382160e+04 |
| 421 | Pacific island small states | PSS | 2017 | 4.376570e+04 |
| 422 | Pacific island small states | PSS | 2016 | 4.370990e+04 |
| 423 | Pacific island small states | PSS | 2015 | 4.365400e+04 |
| 424 | Pacific island small states | PSS | 2014 | 4.359826e+04 |
| 425 | Pacific island small states | PSS | 2013 | 4.354252e+04 |
| 426 | Pacific island small states | PSS | 2012 | 4.348678e+04 |
| 427 | Pacific island small states | PSS | 2011 | 4.343104e+04 |
| 428 | Pacific island small states | PSS | 2010 | 4.337530e+04 |
| 429 | Post-demographic dividend | PST | 2020 | 1.006489e+07 |
| 430 | Post-demographic dividend | PST | 2019 | 1.006308e+07 |
| 431 | Post-demographic dividend | PST | 2018 | 1.006141e+07 |
| 432 | Post-demographic dividend | PST | 2017 | 1.005992e+07 |
| 433 | Post-demographic dividend | PST | 2016 | 1.006136e+07 |
| 434 | Post-demographic dividend | PST | 2015 | 1.004921e+07 |
| 435 | Post-demographic dividend | PST | 2014 | 1.003673e+07 |
| 436 | Post-demographic dividend | PST | 2013 | 1.002425e+07 |
| 437 | Post-demographic dividend | PST | 2012 | 1.001177e+07 |
| 438 | Post-demographic dividend | PST | 2011 | 9.999288e+06 |
| 439 | Post-demographic dividend | PST | 2010 | 9.986807e+06 |
| 440 | Pre-demographic dividend | PRE | 2020 | 5.242009e+06 |
| 441 | Pre-demographic dividend | PRE | 2019 | 5.278468e+06 |
| 442 | Pre-demographic dividend | PRE | 2018 | 5.315324e+06 |
| 443 | Pre-demographic dividend | PRE | 2017 | 5.351162e+06 |
| 444 | Pre-demographic dividend | PRE | 2016 | 5.387374e+06 |
| 445 | Pre-demographic dividend | PRE | 2015 | 5.424418e+06 |
| 446 | Pre-demographic dividend | PRE | 2014 | 5.459906e+06 |
| 447 | Pre-demographic dividend | PRE | 2013 | 5.495393e+06 |
| 448 | Pre-demographic dividend | PRE | 2012 | 5.530880e+06 |
| 449 | Pre-demographic dividend | PRE | 2011 | 5.566367e+06 |
| 450 | Pre-demographic dividend | PRE | 2010 | 5.601854e+06 |
| 451 | Small states | SST | 2020 | 9.911187e+05 |
| 452 | Small states | SST | 2019 | 9.935737e+05 |
| 453 | Small states | SST | 2018 | 9.960297e+05 |
| 454 | Small states | SST | 2017 | 9.984878e+05 |
| 455 | Small states | SST | 2016 | 1.000716e+06 |
| 456 | Small states | SST | 2015 | 1.003163e+06 |
| 457 | Small states | SST | 2014 | 1.005455e+06 |
| 458 | Small states | SST | 2013 | 1.007747e+06 |
| 459 | Small states | SST | 2012 | 1.010038e+06 |
| 460 | Small states | SST | 2011 | 1.012330e+06 |
| 461 | Small states | SST | 2010 | 1.014622e+06 |
| 462 | South Asia | SAS | 2020 | 8.977869e+05 |
| 463 | South Asia | SAS | 2019 | 8.955481e+05 |
| 464 | South Asia | SAS | 2018 | 8.933093e+05 |
| 465 | South Asia | SAS | 2017 | 8.910705e+05 |
| 466 | South Asia | SAS | 2016 | 8.886015e+05 |
| 467 | South Asia | SAS | 2015 | 8.865929e+05 |
| 468 | South Asia | SAS | 2014 | 8.841909e+05 |
| 469 | South Asia | SAS | 2013 | 8.817888e+05 |
| 470 | South Asia | SAS | 2012 | 8.793868e+05 |
| 471 | South Asia | SAS | 2011 | 8.769848e+05 |
| 472 | South Asia | SAS | 2010 | 8.745827e+05 |
| 473 | South Asia (IDA & IBRD) | TSA | 2020 | 8.977869e+05 |
| 474 | South Asia (IDA & IBRD) | TSA | 2019 | 8.955481e+05 |
| 475 | South Asia (IDA & IBRD) | TSA | 2018 | 8.933093e+05 |
| 476 | South Asia (IDA & IBRD) | TSA | 2017 | 8.910705e+05 |
| 477 | South Asia (IDA & IBRD) | TSA | 2016 | 8.886015e+05 |
| 478 | South Asia (IDA & IBRD) | TSA | 2015 | 8.865929e+05 |
| 479 | South Asia (IDA & IBRD) | TSA | 2014 | 8.841909e+05 |
| 480 | South Asia (IDA & IBRD) | TSA | 2013 | 8.817888e+05 |
| 481 | South Asia (IDA & IBRD) | TSA | 2012 | 8.793868e+05 |
| 482 | South Asia (IDA & IBRD) | TSA | 2011 | 8.769848e+05 |
| 483 | South Asia (IDA & IBRD) | TSA | 2010 | 8.745827e+05 |
| 484 | Sub-Saharan Africa | SSF | 2020 | 6.271976e+06 |
| 485 | Sub-Saharan Africa | SSF | 2019 | 6.311896e+06 |
| 486 | Sub-Saharan Africa | SSF | 2018 | 6.352213e+06 |
| 487 | Sub-Saharan Africa | SSF | 2017 | 6.391509e+06 |
| 488 | Sub-Saharan Africa | SSF | 2016 | 6.430837e+06 |
| 489 | Sub-Saharan Africa | SSF | 2015 | 6.470986e+06 |
| 490 | Sub-Saharan Africa | SSF | 2014 | 6.510132e+06 |
| 491 | Sub-Saharan Africa | SSF | 2013 | 6.549278e+06 |
| 492 | Sub-Saharan Africa | SSF | 2012 | 6.588424e+06 |
| 493 | Sub-Saharan Africa | SSF | 2011 | 6.627570e+06 |
| 494 | Sub-Saharan Africa | SSF | 2010 | 6.666716e+06 |
| 495 | Sub-Saharan Africa (excluding high income) | SSA | 2020 | 6.271639e+06 |
| 496 | Sub-Saharan Africa (excluding high income) | SSA | 2019 | 6.311559e+06 |
| 497 | Sub-Saharan Africa (excluding high income) | SSA | 2018 | 6.351876e+06 |
| 498 | Sub-Saharan Africa (excluding high income) | SSA | 2017 | 6.391172e+06 |
| 499 | Sub-Saharan Africa (excluding high income) | SSA | 2016 | 6.430500e+06 |
| 500 | Sub-Saharan Africa (excluding high income) | SSA | 2015 | 6.470650e+06 |
| 501 | Sub-Saharan Africa (excluding high income) | SSA | 2014 | 6.509795e+06 |
| 502 | Sub-Saharan Africa (excluding high income) | SSA | 2013 | 6.548941e+06 |
| 503 | Sub-Saharan Africa (excluding high income) | SSA | 2012 | 6.588087e+06 |
| 504 | Sub-Saharan Africa (excluding high income) | SSA | 2011 | 6.627233e+06 |
| 505 | Sub-Saharan Africa (excluding high income) | SSA | 2010 | 6.666379e+06 |
| 506 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2020 | 6.271976e+06 |
| 507 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2019 | 6.311896e+06 |
| 508 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2018 | 6.352213e+06 |
| 509 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2017 | 6.391509e+06 |
| 510 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2016 | 6.430837e+06 |
| 511 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2015 | 6.470986e+06 |
| 512 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2014 | 6.510132e+06 |
| 513 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2013 | 6.549278e+06 |
| 514 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2012 | 6.588424e+06 |
| 515 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2011 | 6.627570e+06 |
| 516 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2010 | 6.666716e+06 |
| 517 | Upper middle income | 2020 | 2.068960e+07 | |
| 518 | Upper middle income | 2019 | 2.069928e+07 | |
| 519 | Upper middle income | 2018 | 2.070973e+07 | |
| 520 | Upper middle income | 2017 | 2.071789e+07 | |
| 521 | Upper middle income | 2016 | 2.074251e+07 | |
| 522 | Upper middle income | 2015 | 2.074497e+07 | |
| 523 | Upper middle income | 2014 | 2.076082e+07 | |
| 524 | Upper middle income | 2013 | 2.077668e+07 | |
| 525 | Upper middle income | 2012 | 2.079253e+07 | |
| 526 | Upper middle income | 2011 | 2.080838e+07 | |
| 527 | Upper middle income | 2010 | 2.082423e+07 | |
| 528 | World | WLD | 2020 | 4.049969e+07 |
| 529 | World | WLD | 2019 | 4.054878e+07 |
| 530 | World | WLD | 2018 | 4.059955e+07 |
| 531 | World | WLD | 2017 | 4.064787e+07 |
| 532 | World | WLD | 2016 | 4.071630e+07 |
| 533 | World | WLD | 2015 | 4.074891e+07 |
| 534 | World | WLD | 2014 | 4.079379e+07 |
| 535 | World | WLD | 2013 | 4.083866e+07 |
| 536 | World | WLD | 2012 | 4.088353e+07 |
| 537 | World | WLD | 2011 | 4.092840e+07 |
| 538 | World | WLD | 2010 | 4.097326e+07 |
| 539 | Afghanistan | AFG | 2020 | 1.208440e+04 |
| 540 | Afghanistan | AFG | 2019 | 1.208440e+04 |
| 541 | Afghanistan | AFG | 2018 | 1.208440e+04 |
| 542 | Afghanistan | AFG | 2017 | 1.208440e+04 |
| 543 | Afghanistan | AFG | 2016 | 1.208440e+04 |
| 544 | Afghanistan | AFG | 2015 | 1.208440e+04 |
| 545 | Afghanistan | AFG | 2014 | 1.208440e+04 |
| 546 | Afghanistan | AFG | 2013 | 1.208440e+04 |
| 547 | Afghanistan | AFG | 2012 | 1.208440e+04 |
| 548 | Afghanistan | AFG | 2011 | 1.208440e+04 |
| 549 | Afghanistan | AFG | 2010 | 1.208440e+04 |
| 550 | Albania | ALB | 2020 | 7.889000e+03 |
| 551 | Albania | ALB | 2019 | 7.889000e+03 |
| 552 | Albania | ALB | 2018 | 7.889000e+03 |
| 553 | Albania | ALB | 2017 | 7.889025e+03 |
| 554 | Albania | ALB | 2016 | 7.891800e+03 |
| 555 | Albania | ALB | 2015 | 7.891875e+03 |
| 556 | Albania | ALB | 2014 | 7.877640e+03 |
| 557 | Albania | ALB | 2013 | 7.863405e+03 |
| 558 | Albania | ALB | 2012 | 7.849170e+03 |
| 559 | Albania | ALB | 2011 | 7.834935e+03 |
| 560 | Albania | ALB | 2010 | 7.820700e+03 |
| 561 | Algeria | DZA | 2020 | 1.949000e+04 |
| 562 | Algeria | DZA | 2019 | 1.939000e+04 |
| 563 | Algeria | DZA | 2018 | 1.930000e+04 |
| 564 | Algeria | DZA | 2017 | 1.943000e+04 |
| 565 | Algeria | DZA | 2016 | 1.956000e+04 |
| 566 | Algeria | DZA | 2015 | 1.956000e+04 |
| 567 | Algeria | DZA | 2014 | 1.948400e+04 |
| 568 | Algeria | DZA | 2013 | 1.940800e+04 |
| 569 | Algeria | DZA | 2012 | 1.933200e+04 |
| 570 | Algeria | DZA | 2011 | 1.925600e+04 |
| 571 | Algeria | DZA | 2010 | 1.918000e+04 |
| 572 | American Samoa | ASM | 2020 | 1.713000e+02 |
| 573 | American Samoa | ASM | 2019 | 1.716000e+02 |
| 574 | American Samoa | ASM | 2018 | 1.719000e+02 |
| 575 | American Samoa | ASM | 2017 | 1.722000e+02 |
| 576 | American Samoa | ASM | 2016 | 1.725000e+02 |
| 577 | American Samoa | ASM | 2015 | 1.728000e+02 |
| 578 | American Samoa | ASM | 2014 | 1.731000e+02 |
| 579 | American Samoa | ASM | 2013 | 1.734000e+02 |
| 580 | American Samoa | ASM | 2012 | 1.737000e+02 |
| 581 | American Samoa | ASM | 2011 | 1.740000e+02 |
| 582 | American Samoa | ASM | 2010 | 1.743000e+02 |
| 583 | Andorra | AND | 2020 | 1.600000e+02 |
| 584 | Andorra | AND | 2019 | 1.600000e+02 |
| 585 | Andorra | AND | 2018 | 1.600000e+02 |
| 586 | Andorra | AND | 2017 | 1.600000e+02 |
| 587 | Andorra | AND | 2016 | 1.600000e+02 |
| 588 | Andorra | AND | 2015 | 1.600000e+02 |
| 589 | Andorra | AND | 2014 | 1.600000e+02 |
| 590 | Andorra | AND | 2013 | 1.600000e+02 |
| 591 | Andorra | AND | 2012 | 1.600000e+02 |
| 592 | Andorra | AND | 2011 | 1.600000e+02 |
| 593 | Andorra | AND | 2010 | 1.600000e+02 |
| 594 | Angola | AGO | 2020 | 6.660738e+05 |
| 595 | Angola | AGO | 2019 | 6.716244e+05 |
| 596 | Angola | AGO | 2018 | 6.771751e+05 |
| 597 | Angola | AGO | 2017 | 6.827257e+05 |
| 598 | Angola | AGO | 2016 | 6.882762e+05 |
| 599 | Angola | AGO | 2015 | 6.938269e+05 |
| 600 | Angola | AGO | 2014 | 6.993775e+05 |
| 601 | Angola | AGO | 2013 | 7.049281e+05 |
| 602 | Angola | AGO | 2012 | 7.104788e+05 |
| 603 | Angola | AGO | 2011 | 7.160294e+05 |
| 604 | Angola | AGO | 2010 | 7.215800e+05 |
| 605 | Antigua and Barbuda | ATG | 2020 | 8.120000e+01 |
| 606 | Antigua and Barbuda | ATG | 2019 | 8.180000e+01 |
| 607 | Antigua and Barbuda | ATG | 2018 | 8.250000e+01 |
| 608 | Antigua and Barbuda | ATG | 2017 | 8.320000e+01 |
| 609 | Antigua and Barbuda | ATG | 2016 | 8.380000e+01 |
| 610 | Antigua and Barbuda | ATG | 2015 | 8.450000e+01 |
| 611 | Antigua and Barbuda | ATG | 2014 | 8.516000e+01 |
| 612 | Antigua and Barbuda | ATG | 2013 | 8.582000e+01 |
| 613 | Antigua and Barbuda | ATG | 2012 | 8.648000e+01 |
| 614 | Antigua and Barbuda | ATG | 2011 | 8.714000e+01 |
| 615 | Antigua and Barbuda | ATG | 2010 | 8.780000e+01 |
| 616 | Argentina | ARG | 2020 | 2.857300e+05 |
| 617 | Argentina | ARG | 2019 | 2.868100e+05 |
| 618 | Argentina | ARG | 2018 | 2.879100e+05 |
| 619 | Argentina | ARG | 2017 | 2.889900e+05 |
| 620 | Argentina | ARG | 2016 | 2.901000e+05 |
| 621 | Argentina | ARG | 2015 | 2.909700e+05 |
| 622 | Argentina | ARG | 2014 | 2.932040e+05 |
| 623 | Argentina | ARG | 2013 | 2.954380e+05 |
| 624 | Argentina | ARG | 2012 | 2.976720e+05 |
| 625 | Argentina | ARG | 2011 | 2.999060e+05 |
| 626 | Argentina | ARG | 2010 | 3.021400e+05 |
| 627 | Armenia | ARM | 2020 | 3.284700e+03 |
| 628 | Armenia | ARM | 2019 | 3.286800e+03 |
| 629 | Armenia | ARM | 2018 | 3.288900e+03 |
| 630 | Armenia | ARM | 2017 | 3.291000e+03 |
| 631 | Armenia | ARM | 2016 | 3.293100e+03 |
| 632 | Armenia | ARM | 2015 | 3.295200e+03 |
| 633 | Armenia | ARM | 2014 | 3.297280e+03 |
| 634 | Armenia | ARM | 2013 | 3.299360e+03 |
| 635 | Armenia | ARM | 2012 | 3.301440e+03 |
| 636 | Armenia | ARM | 2011 | 3.303520e+03 |
| 637 | Armenia | ARM | 2010 | 3.305600e+03 |
| 638 | Aruba | ABW | 2020 | 4.200000e+00 |
| 639 | Aruba | ABW | 2019 | 4.200000e+00 |
| 640 | Aruba | ABW | 2018 | 4.200000e+00 |
| 641 | Aruba | ABW | 2017 | 4.200000e+00 |
| 642 | Aruba | ABW | 2016 | 4.200000e+00 |
| 643 | Aruba | ABW | 2015 | 4.200000e+00 |
| 644 | Aruba | ABW | 2014 | 4.200000e+00 |
| 645 | Aruba | ABW | 2013 | 4.200000e+00 |
| 646 | Aruba | ABW | 2012 | 4.200000e+00 |
| 647 | Aruba | ABW | 2011 | 4.200000e+00 |
| 648 | Aruba | ABW | 2010 | 4.200000e+00 |
| 649 | Australia | AUS | 2020 | 1.340051e+06 |
| 650 | Australia | AUS | 2019 | 1.340051e+06 |
| 651 | Australia | AUS | 2018 | 1.340051e+06 |
| 652 | Australia | AUS | 2017 | 1.340174e+06 |
| 653 | Australia | AUS | 2016 | 1.340372e+06 |
| 654 | Australia | AUS | 2015 | 1.330945e+06 |
| 655 | Australia | AUS | 2014 | 1.323848e+06 |
| 656 | Australia | AUS | 2013 | 1.316751e+06 |
| 657 | Australia | AUS | 2012 | 1.309655e+06 |
| 658 | Australia | AUS | 2011 | 1.302558e+06 |
| 659 | Australia | AUS | 2010 | 1.295461e+06 |
| 660 | Austria | AUT | 2020 | 3.899150e+04 |
| 661 | Austria | AUT | 2019 | 3.895560e+04 |
| 662 | Austria | AUT | 2018 | 3.891970e+04 |
| 663 | Austria | AUT | 2017 | 3.888380e+04 |
| 664 | Austria | AUT | 2016 | 3.884790e+04 |
| 665 | Austria | AUT | 2015 | 3.881190e+04 |
| 666 | Austria | AUT | 2014 | 3.877592e+04 |
| 667 | Austria | AUT | 2013 | 3.873994e+04 |
| 668 | Austria | AUT | 2012 | 3.870396e+04 |
| 669 | Austria | AUT | 2011 | 3.866798e+04 |
| 670 | Austria | AUT | 2010 | 3.863200e+04 |
| 671 | Azerbaijan | AZE | 2020 | 1.131770e+04 |
| 672 | Azerbaijan | AZE | 2019 | 1.120240e+04 |
| 673 | Azerbaijan | AZE | 2018 | 1.108715e+04 |
| 674 | Azerbaijan | AZE | 2017 | 1.097185e+04 |
| 675 | Azerbaijan | AZE | 2016 | 1.087475e+04 |
| 676 | Azerbaijan | AZE | 2015 | 1.077887e+04 |
| 677 | Azerbaijan | AZE | 2014 | 1.068808e+04 |
| 678 | Azerbaijan | AZE | 2013 | 1.059730e+04 |
| 679 | Azerbaijan | AZE | 2012 | 1.050651e+04 |
| 680 | Azerbaijan | AZE | 2011 | 1.041573e+04 |
| 681 | Azerbaijan | AZE | 2010 | 1.032495e+04 |
| 682 | Bahamas, The | BHS | 2020 | 5.098600e+03 |
| 683 | Bahamas, The | BHS | 2019 | 5.098600e+03 |
| 684 | Bahamas, The | BHS | 2018 | 5.098600e+03 |
| 685 | Bahamas, The | BHS | 2017 | 5.098600e+03 |
| 686 | Bahamas, The | BHS | 2016 | 5.098600e+03 |
| 687 | Bahamas, The | BHS | 2015 | 5.098600e+03 |
| 688 | Bahamas, The | BHS | 2014 | 5.098600e+03 |
| 689 | Bahamas, The | BHS | 2013 | 5.098600e+03 |
| 690 | Bahamas, The | BHS | 2012 | 5.098600e+03 |
| 691 | Bahamas, The | BHS | 2011 | 5.098600e+03 |
| 692 | Bahamas, The | BHS | 2010 | 5.098600e+03 |
| 693 | Bahrain | BHR | 2020 | 7.000000e+00 |
| 694 | Bahrain | BHR | 2019 | 6.800000e+00 |
| 695 | Bahrain | BHR | 2018 | 6.600000e+00 |
| 696 | Bahrain | BHR | 2017 | 6.400000e+00 |
| 697 | Bahrain | BHR | 2016 | 6.200000e+00 |
| 698 | Bahrain | BHR | 2015 | 6.000000e+00 |
| 699 | Bahrain | BHR | 2014 | 5.840000e+00 |
| 700 | Bahrain | BHR | 2013 | 5.680000e+00 |
| 701 | Bahrain | BHR | 2012 | 5.520000e+00 |
| 702 | Bahrain | BHR | 2011 | 5.360000e+00 |
| 703 | Bahrain | BHR | 2010 | 5.200000e+00 |
| 704 | Bangladesh | BGD | 2020 | 1.883400e+04 |
| 705 | Bangladesh | BGD | 2019 | 1.883400e+04 |
| 706 | Bangladesh | BGD | 2018 | 1.883400e+04 |
| 707 | Bangladesh | BGD | 2017 | 1.883400e+04 |
| 708 | Bangladesh | BGD | 2016 | 1.883400e+04 |
| 709 | Bangladesh | BGD | 2015 | 1.883400e+04 |
| 710 | Bangladesh | BGD | 2014 | 1.884388e+04 |
| 711 | Bangladesh | BGD | 2013 | 1.885377e+04 |
| 712 | Bangladesh | BGD | 2012 | 1.886365e+04 |
| 713 | Bangladesh | BGD | 2011 | 1.887354e+04 |
| 714 | Bangladesh | BGD | 2010 | 1.888342e+04 |
| 715 | Barbados | BRB | 2020 | 6.300000e+01 |
| 716 | Barbados | BRB | 2019 | 6.300000e+01 |
| 717 | Barbados | BRB | 2018 | 6.300000e+01 |
| 718 | Barbados | BRB | 2017 | 6.300000e+01 |
| 719 | Barbados | BRB | 2016 | 6.300000e+01 |
| 720 | Barbados | BRB | 2015 | 6.300000e+01 |
| 721 | Barbados | BRB | 2014 | 6.300000e+01 |
| 722 | Barbados | BRB | 2013 | 6.300000e+01 |
| 723 | Barbados | BRB | 2012 | 6.300000e+01 |
| 724 | Barbados | BRB | 2011 | 6.300000e+01 |
| 725 | Barbados | BRB | 2010 | 6.300000e+01 |
| 726 | Belarus | BLR | 2020 | 8.767600e+04 |
| 727 | Belarus | BLR | 2019 | 8.753100e+04 |
| 728 | Belarus | BLR | 2018 | 8.738600e+04 |
| 729 | Belarus | BLR | 2017 | 8.724100e+04 |
| 730 | Belarus | BLR | 2016 | 8.709600e+04 |
| 731 | Belarus | BLR | 2015 | 8.633500e+04 |
| 732 | Belarus | BLR | 2014 | 8.632800e+04 |
| 733 | Belarus | BLR | 2013 | 8.632100e+04 |
| 734 | Belarus | BLR | 2012 | 8.631400e+04 |
| 735 | Belarus | BLR | 2011 | 8.630700e+04 |
| 736 | Belarus | BLR | 2010 | 8.630000e+04 |
| 737 | Belgium | BEL | 2020 | 6.893000e+03 |
| 738 | Belgium | BEL | 2019 | 6.893000e+03 |
| 739 | Belgium | BEL | 2018 | 6.893000e+03 |
| 740 | Belgium | BEL | 2017 | 6.893000e+03 |
| 741 | Belgium | BEL | 2016 | 6.893000e+03 |
| 742 | Belgium | BEL | 2015 | 6.893000e+03 |
| 743 | Belgium | BEL | 2014 | 6.894140e+03 |
| 744 | Belgium | BEL | 2013 | 6.895280e+03 |
| 745 | Belgium | BEL | 2012 | 6.896420e+03 |
| 746 | Belgium | BEL | 2011 | 6.897560e+03 |
| 747 | Belgium | BEL | 2010 | 6.898700e+03 |
| 748 | Belize | BLZ | 2020 | 1.277050e+04 |
| 749 | Belize | BLZ | 2019 | 1.288210e+04 |
| 750 | Belize | BLZ | 2018 | 1.299370e+04 |
| 751 | Belize | BLZ | 2017 | 1.310520e+04 |
| 752 | Belize | BLZ | 2016 | 1.321680e+04 |
| 753 | Belize | BLZ | 2015 | 1.332830e+04 |
| 754 | Belize | BLZ | 2014 | 1.344542e+04 |
| 755 | Belize | BLZ | 2013 | 1.356254e+04 |
| 756 | Belize | BLZ | 2012 | 1.367966e+04 |
| 757 | Belize | BLZ | 2011 | 1.379678e+04 |
| 758 | Belize | BLZ | 2010 | 1.391390e+04 |
| 759 | Benin | BEN | 2020 | 3.135150e+04 |
| 760 | Benin | BEN | 2019 | 3.185150e+04 |
| 761 | Benin | BEN | 2018 | 3.235150e+04 |
| 762 | Benin | BEN | 2017 | 3.285150e+04 |
| 763 | Benin | BEN | 2016 | 3.335150e+04 |
| 764 | Benin | BEN | 2015 | 3.385150e+04 |
| 765 | Benin | BEN | 2014 | 3.435150e+04 |
| 766 | Benin | BEN | 2013 | 3.485150e+04 |
| 767 | Benin | BEN | 2012 | 3.535150e+04 |
| 768 | Benin | BEN | 2011 | 3.585150e+04 |
| 769 | Benin | BEN | 2010 | 3.635150e+04 |
| 770 | Bermuda | BMU | 2020 | 1.000000e+01 |
| 771 | Bermuda | BMU | 2019 | 1.000000e+01 |
| 772 | Bermuda | BMU | 2018 | 1.000000e+01 |
| 773 | Bermuda | BMU | 2017 | 1.000000e+01 |
| 774 | Bermuda | BMU | 2016 | 1.000000e+01 |
| 775 | Bermuda | BMU | 2015 | 1.000000e+01 |
| 776 | Bermuda | BMU | 2014 | 1.000000e+01 |
| 777 | Bermuda | BMU | 2013 | 1.000000e+01 |
| 778 | Bermuda | BMU | 2012 | 1.000000e+01 |
| 779 | Bermuda | BMU | 2011 | 1.000000e+01 |
| 780 | Bermuda | BMU | 2010 | 1.000000e+01 |
| 781 | Bhutan | BTN | 2020 | 2.725080e+04 |
| 782 | Bhutan | BTN | 2019 | 2.723100e+04 |
| 783 | Bhutan | BTN | 2018 | 2.721120e+04 |
| 784 | Bhutan | BTN | 2017 | 2.719140e+04 |
| 785 | Bhutan | BTN | 2016 | 2.717160e+04 |
| 786 | Bhutan | BTN | 2015 | 2.715180e+04 |
| 787 | Bhutan | BTN | 2014 | 2.713202e+04 |
| 788 | Bhutan | BTN | 2013 | 2.711224e+04 |
| 789 | Bhutan | BTN | 2012 | 2.709246e+04 |
| 790 | Bhutan | BTN | 2011 | 2.707268e+04 |
| 791 | Bhutan | BTN | 2010 | 2.705290e+04 |
| 792 | Bolivia | BOL | 2020 | 5.083376e+05 |
| 793 | Bolivia | BOL | 2019 | 5.103376e+05 |
| 794 | Bolivia | BOL | 2018 | 5.125324e+05 |
| 795 | Bolivia | BOL | 2017 | 5.149222e+05 |
| 796 | Bolivia | BOL | 2016 | 5.175068e+05 |
| 797 | Bolivia | BOL | 2015 | 5.202722e+05 |
| 798 | Bolivia | BOL | 2014 | 5.223898e+05 |
| 799 | Bolivia | BOL | 2013 | 5.245074e+05 |
| 800 | Bolivia | BOL | 2012 | 5.266249e+05 |
| 801 | Bolivia | BOL | 2011 | 5.287425e+05 |
| 802 | Bolivia | BOL | 2010 | 5.308601e+05 |
| 803 | Bosnia and Herzegovina | BIH | 2020 | 2.187910e+04 |
| 804 | Bosnia and Herzegovina | BIH | 2019 | 2.187910e+04 |
| 805 | Bosnia and Herzegovina | BIH | 2018 | 2.187910e+04 |
| 806 | Bosnia and Herzegovina | BIH | 2017 | 2.187910e+04 |
| 807 | Bosnia and Herzegovina | BIH | 2016 | 2.176510e+04 |
| 808 | Bosnia and Herzegovina | BIH | 2015 | 2.160500e+04 |
| 809 | Bosnia and Herzegovina | BIH | 2014 | 2.148932e+04 |
| 810 | Bosnia and Herzegovina | BIH | 2013 | 2.137364e+04 |
| 811 | Bosnia and Herzegovina | BIH | 2012 | 2.125796e+04 |
| 812 | Bosnia and Herzegovina | BIH | 2011 | 2.114228e+04 |
| 813 | Bosnia and Herzegovina | BIH | 2010 | 2.102660e+04 |
| 814 | Botswana | BWA | 2020 | 1.525470e+05 |
| 815 | Botswana | BWA | 2019 | 1.537300e+05 |
| 816 | Botswana | BWA | 2018 | 1.549130e+05 |
| 817 | Botswana | BWA | 2017 | 1.560960e+05 |
| 818 | Botswana | BWA | 2016 | 1.572790e+05 |
| 819 | Botswana | BWA | 2015 | 1.584620e+05 |
| 820 | Botswana | BWA | 2014 | 1.596450e+05 |
| 821 | Botswana | BWA | 2013 | 1.608280e+05 |
| 822 | Botswana | BWA | 2012 | 1.620110e+05 |
| 823 | Botswana | BWA | 2011 | 1.631940e+05 |
| 824 | Botswana | BWA | 2010 | 1.643770e+05 |
| 825 | Brazil | BRA | 2020 | 4.966196e+06 |
| 826 | Brazil | BRA | 2019 | 4.977985e+06 |
| 827 | Brazil | BRA | 2018 | 4.990514e+06 |
| 828 | Brazil | BRA | 2017 | 5.000916e+06 |
| 829 | Brazil | BRA | 2016 | 5.020821e+06 |
| 830 | Brazil | BRA | 2015 | 5.038848e+06 |
| 831 | Brazil | BRA | 2014 | 5.054240e+06 |
| 832 | Brazil | BRA | 2013 | 5.069632e+06 |
| 833 | Brazil | BRA | 2012 | 5.085023e+06 |
| 834 | Brazil | BRA | 2011 | 5.100415e+06 |
| 835 | Brazil | BRA | 2010 | 5.115807e+06 |
| 836 | British Virgin Islands | VGB | 2020 | 3.620000e+01 |
| 837 | British Virgin Islands | VGB | 2019 | 3.620000e+01 |
| 838 | British Virgin Islands | VGB | 2018 | 3.620000e+01 |
| 839 | British Virgin Islands | VGB | 2017 | 3.620000e+01 |
| 840 | British Virgin Islands | VGB | 2016 | 3.620000e+01 |
| 841 | British Virgin Islands | VGB | 2015 | 3.620000e+01 |
| 842 | British Virgin Islands | VGB | 2014 | 3.624000e+01 |
| 843 | British Virgin Islands | VGB | 2013 | 3.628000e+01 |
| 844 | British Virgin Islands | VGB | 2012 | 3.632000e+01 |
| 845 | British Virgin Islands | VGB | 2011 | 3.636000e+01 |
| 846 | British Virgin Islands | VGB | 2010 | 3.640000e+01 |
| 847 | Brunei Darussalam | BRN | 2020 | 3.800000e+03 |
| 848 | Brunei Darussalam | BRN | 2019 | 3.800000e+03 |
| 849 | Brunei Darussalam | BRN | 2018 | 3.800000e+03 |
| 850 | Brunei Darussalam | BRN | 2017 | 3.800000e+03 |
| 851 | Brunei Darussalam | BRN | 2016 | 3.800000e+03 |
| 852 | Brunei Darussalam | BRN | 2015 | 3.800000e+03 |
| 853 | Brunei Darussalam | BRN | 2014 | 3.800000e+03 |
| 854 | Brunei Darussalam | BRN | 2013 | 3.800000e+03 |
| 855 | Brunei Darussalam | BRN | 2012 | 3.800000e+03 |
| 856 | Brunei Darussalam | BRN | 2011 | 3.800000e+03 |
| 857 | Brunei Darussalam | BRN | 2010 | 3.800000e+03 |
| 858 | Bulgaria | BGR | 2020 | 3.893000e+04 |
| 859 | Bulgaria | BGR | 2019 | 3.880000e+04 |
| 860 | Bulgaria | BGR | 2018 | 3.867000e+04 |
| 861 | Bulgaria | BGR | 2017 | 3.854000e+04 |
| 862 | Bulgaria | BGR | 2016 | 3.841000e+04 |
| 863 | Bulgaria | BGR | 2015 | 3.833000e+04 |
| 864 | Bulgaria | BGR | 2014 | 3.813800e+04 |
| 865 | Bulgaria | BGR | 2013 | 3.794600e+04 |
| 866 | Bulgaria | BGR | 2012 | 3.775400e+04 |
| 867 | Bulgaria | BGR | 2011 | 3.756200e+04 |
| 868 | Bulgaria | BGR | 2010 | 3.737000e+04 |
| 869 | Burkina Faso | BFA | 2020 | 6.216400e+04 |
| 870 | Burkina Faso | BFA | 2019 | 6.266400e+04 |
| 871 | Burkina Faso | BFA | 2018 | 6.316400e+04 |
| 872 | Burkina Faso | BFA | 2017 | 6.366400e+04 |
| 873 | Burkina Faso | BFA | 2016 | 6.416400e+04 |
| 874 | Burkina Faso | BFA | 2015 | 6.466400e+04 |
| 875 | Burkina Faso | BFA | 2014 | 6.516420e+04 |
| 876 | Burkina Faso | BFA | 2013 | 6.566440e+04 |
| 877 | Burkina Faso | BFA | 2012 | 6.616460e+04 |
| 878 | Burkina Faso | BFA | 2011 | 6.666480e+04 |
| 879 | Burkina Faso | BFA | 2010 | 6.716500e+04 |
| 880 | Burundi | BDI | 2020 | 2.796400e+03 |
| 881 | Burundi | BDI | 2019 | 2.796400e+03 |
| 882 | Burundi | BDI | 2018 | 2.796400e+03 |
| 883 | Burundi | BDI | 2017 | 2.796400e+03 |
| 884 | Burundi | BDI | 2016 | 2.796400e+03 |
| 885 | Burundi | BDI | 2015 | 2.796400e+03 |
| 886 | Burundi | BDI | 2014 | 2.625000e+03 |
| 887 | Burundi | BDI | 2013 | 2.453600e+03 |
| 888 | Burundi | BDI | 2012 | 2.282200e+03 |
| 889 | Burundi | BDI | 2011 | 2.110800e+03 |
| 890 | Burundi | BDI | 2010 | 1.939400e+03 |
| 891 | Cabo Verde | CPV | 2020 | 4.572000e+02 |
| 892 | Cabo Verde | CPV | 2019 | 4.542000e+02 |
| 893 | Cabo Verde | CPV | 2018 | 4.512000e+02 |
| 894 | Cabo Verde | CPV | 2017 | 4.482000e+02 |
| 895 | Cabo Verde | CPV | 2016 | 4.452000e+02 |
| 896 | Cabo Verde | CPV | 2015 | 4.422000e+02 |
| 897 | Cabo Verde | CPV | 2014 | 4.392000e+02 |
| 898 | Cabo Verde | CPV | 2013 | 4.362000e+02 |
| 899 | Cabo Verde | CPV | 2012 | 4.332000e+02 |
| 900 | Cabo Verde | CPV | 2011 | 4.302000e+02 |
| 901 | Cabo Verde | CPV | 2010 | 4.272000e+02 |
| 902 | Cambodia | KHM | 2020 | 8.068370e+04 |
| 903 | Cambodia | KHM | 2019 | 8.224060e+04 |
| 904 | Cambodia | KHM | 2018 | 8.379750e+04 |
| 905 | Cambodia | KHM | 2017 | 8.535440e+04 |
| 906 | Cambodia | KHM | 2016 | 8.691130e+04 |
| 907 | Cambodia | KHM | 2015 | 8.846820e+04 |
| 908 | Cambodia | KHM | 2014 | 9.195302e+04 |
| 909 | Cambodia | KHM | 2013 | 9.543784e+04 |
| 910 | Cambodia | KHM | 2012 | 9.892266e+04 |
| 911 | Cambodia | KHM | 2011 | 1.024075e+05 |
| 912 | Cambodia | KHM | 2010 | 1.058923e+05 |
| 913 | Cameroon | CMR | 2020 | 2.034048e+05 |
| 914 | Cameroon | CMR | 2019 | 2.039648e+05 |
| 915 | Cameroon | CMR | 2018 | 2.045248e+05 |
| 916 | Cameroon | CMR | 2017 | 2.050848e+05 |
| 917 | Cameroon | CMR | 2016 | 2.056448e+05 |
| 918 | Cameroon | CMR | 2015 | 2.062048e+05 |
| 919 | Cameroon | CMR | 2014 | 2.067648e+05 |
| 920 | Cameroon | CMR | 2013 | 2.073248e+05 |
| 921 | Cameroon | CMR | 2012 | 2.078848e+05 |
| 922 | Cameroon | CMR | 2011 | 2.084448e+05 |
| 923 | Cameroon | CMR | 2010 | 2.090048e+05 |
| 924 | Canada | CAN | 2020 | 3.469281e+06 |
| 925 | Canada | CAN | 2019 | 3.469651e+06 |
| 926 | Canada | CAN | 2018 | 3.470021e+06 |
| 927 | Canada | CAN | 2017 | 3.470390e+06 |
| 928 | Canada | CAN | 2016 | 3.470760e+06 |
| 929 | Canada | CAN | 2015 | 3.471157e+06 |
| 930 | Canada | CAN | 2014 | 3.471570e+06 |
| 931 | Canada | CAN | 2013 | 3.471983e+06 |
| 932 | Canada | CAN | 2012 | 3.472396e+06 |
| 933 | Canada | CAN | 2011 | 3.472809e+06 |
| 934 | Canada | CAN | 2010 | 3.473222e+06 |
| 935 | Cayman Islands | CYM | 2020 | 1.272000e+02 |
| 936 | Cayman Islands | CYM | 2019 | 1.272000e+02 |
| 937 | Cayman Islands | CYM | 2018 | 1.281000e+02 |
| 938 | Cayman Islands | CYM | 2017 | 1.272000e+02 |
| 939 | Cayman Islands | CYM | 2016 | 1.272000e+02 |
| 940 | Cayman Islands | CYM | 2015 | 1.272000e+02 |
| 941 | Cayman Islands | CYM | 2014 | 1.272000e+02 |
| 942 | Cayman Islands | CYM | 2013 | 1.272000e+02 |
| 943 | Cayman Islands | CYM | 2012 | 1.272000e+02 |
| 944 | Cayman Islands | CYM | 2011 | 1.272000e+02 |
| 945 | Cayman Islands | CYM | 2010 | 1.272000e+02 |
| 946 | Central African Republic | CAF | 2020 | 2.230300e+05 |
| 947 | Central African Republic | CAF | 2019 | 2.233300e+05 |
| 948 | Central African Republic | CAF | 2018 | 2.236300e+05 |
| 949 | Central African Republic | CAF | 2017 | 2.239300e+05 |
| 950 | Central African Republic | CAF | 2016 | 2.242300e+05 |
| 951 | Central African Republic | CAF | 2015 | 2.245300e+05 |
| 952 | Central African Republic | CAF | 2014 | 2.248300e+05 |
| 953 | Central African Republic | CAF | 2013 | 2.251300e+05 |
| 954 | Central African Republic | CAF | 2012 | 2.254300e+05 |
| 955 | Central African Republic | CAF | 2011 | 2.257300e+05 |
| 956 | Central African Republic | CAF | 2010 | 2.260300e+05 |
| 957 | Chad | TCD | 2020 | 4.313000e+04 |
| 958 | Chad | TCD | 2019 | 4.422000e+04 |
| 959 | Chad | TCD | 2018 | 4.535000e+04 |
| 960 | Chad | TCD | 2017 | 4.651000e+04 |
| 961 | Chad | TCD | 2016 | 4.769000e+04 |
| 962 | Chad | TCD | 2015 | 4.890000e+04 |
| 963 | Chad | TCD | 2014 | 5.018000e+04 |
| 964 | Chad | TCD | 2013 | 5.146000e+04 |
| 965 | Chad | TCD | 2012 | 5.274000e+04 |
| 966 | Chad | TCD | 2011 | 5.402000e+04 |
| 967 | Chad | TCD | 2010 | 5.530000e+04 |
| 968 | Channel Islands | CHI | 2020 | 1.020000e+01 |
| 969 | Channel Islands | CHI | 2019 | 1.020000e+01 |
| 970 | Channel Islands | CHI | 2018 | 1.020000e+01 |
| 971 | Channel Islands | CHI | 2017 | 1.020000e+01 |
| 972 | Channel Islands | CHI | 2016 | 1.020000e+01 |
| 973 | Channel Islands | CHI | 2015 | 1.020000e+01 |
| 974 | Channel Islands | CHI | 2014 | 1.020000e+01 |
| 975 | Channel Islands | CHI | 2013 | 1.020000e+01 |
| 976 | Channel Islands | CHI | 2012 | 1.020000e+01 |
| 977 | Channel Islands | CHI | 2011 | 1.020000e+01 |
| 978 | Channel Islands | CHI | 2010 | 1.020000e+01 |
| 979 | Chile | CHL | 2020 | 1.821070e+05 |
| 980 | Chile | CHL | 2019 | 1.808780e+05 |
| 981 | Chile | CHL | 2018 | 1.796487e+05 |
| 982 | Chile | CHL | 2017 | 1.784194e+05 |
| 983 | Chile | CHL | 2016 | 1.771901e+05 |
| 984 | Chile | CHL | 2015 | 1.759608e+05 |
| 985 | Chile | CHL | 2014 | 1.742192e+05 |
| 986 | Chile | CHL | 2013 | 1.724775e+05 |
| 987 | Chile | CHL | 2012 | 1.707359e+05 |
| 988 | Chile | CHL | 2011 | 1.689942e+05 |
| 989 | Chile | CHL | 2010 | 1.672526e+05 |
| 990 | China | CHN | 2020 | 2.199782e+06 |
| 991 | China | CHN | 2019 | 2.180986e+06 |
| 992 | China | CHN | 2018 | 2.162190e+06 |
| 993 | China | CHN | 2017 | 2.143395e+06 |
| 994 | China | CHN | 2016 | 2.124599e+06 |
| 995 | China | CHN | 2015 | 2.102942e+06 |
| 996 | China | CHN | 2014 | 2.083575e+06 |
| 997 | China | CHN | 2013 | 2.064207e+06 |
| 998 | China | CHN | 2012 | 2.044839e+06 |
| 999 | China | CHN | 2011 | 2.025472e+06 |
| 1000 | China | CHN | 2010 | 2.006104e+06 |
| 1001 | Colombia | COL | 2020 | 5.914191e+05 |
| 1002 | Colombia | COL | 2019 | 5.934120e+05 |
| 1003 | Colombia | COL | 2018 | 5.954048e+05 |
| 1004 | Colombia | COL | 2017 | 5.973977e+05 |
| 1005 | Colombia | COL | 2016 | 5.995949e+05 |
| 1006 | Colombia | COL | 2015 | 6.013466e+05 |
| 1007 | Colombia | COL | 2014 | 6.026929e+05 |
| 1008 | Colombia | COL | 2013 | 6.040391e+05 |
| 1009 | Colombia | COL | 2012 | 6.053854e+05 |
| 1010 | Colombia | COL | 2011 | 6.067316e+05 |
| 1011 | Colombia | COL | 2010 | 6.080779e+05 |
| 1012 | Comoros | COM | 2020 | 3.292000e+02 |
| 1013 | Comoros | COM | 2019 | 3.336000e+02 |
| 1014 | Comoros | COM | 2018 | 3.380000e+02 |
| 1015 | Comoros | COM | 2017 | 3.423000e+02 |
| 1016 | Comoros | COM | 2016 | 3.467000e+02 |
| 1017 | Comoros | COM | 2015 | 3.511000e+02 |
| 1018 | Comoros | COM | 2014 | 3.554800e+02 |
| 1019 | Comoros | COM | 2013 | 3.598600e+02 |
| 1020 | Comoros | COM | 2012 | 3.642400e+02 |
| 1021 | Comoros | COM | 2011 | 3.686200e+02 |
| 1022 | Comoros | COM | 2010 | 3.730000e+02 |
| 1023 | Congo, Dem. Rep. | COD | 2020 | 1.261552e+06 |
| 1024 | Congo, Dem. Rep. | COD | 2019 | 1.272566e+06 |
| 1025 | Congo, Dem. Rep. | COD | 2018 | 1.283580e+06 |
| 1026 | Congo, Dem. Rep. | COD | 2017 | 1.294594e+06 |
| 1027 | Congo, Dem. Rep. | COD | 2016 | 1.305607e+06 |
| 1028 | Congo, Dem. Rep. | COD | 2015 | 1.316621e+06 |
| 1029 | Congo, Dem. Rep. | COD | 2014 | 1.327635e+06 |
| 1030 | Congo, Dem. Rep. | COD | 2013 | 1.338649e+06 |
| 1031 | Congo, Dem. Rep. | COD | 2012 | 1.349662e+06 |
| 1032 | Congo, Dem. Rep. | COD | 2011 | 1.360676e+06 |
| 1033 | Congo, Dem. Rep. | COD | 2010 | 1.371690e+06 |
| 1034 | Congo, Rep. | COG | 2020 | 2.194600e+05 |
| 1035 | Congo, Rep. | COG | 2019 | 2.196100e+05 |
| 1036 | Congo, Rep. | COG | 2018 | 2.197600e+05 |
| 1037 | Congo, Rep. | COG | 2017 | 2.199100e+05 |
| 1038 | Congo, Rep. | COG | 2016 | 2.200300e+05 |
| 1039 | Congo, Rep. | COG | 2015 | 2.201500e+05 |
| 1040 | Congo, Rep. | COG | 2014 | 2.202700e+05 |
| 1041 | Congo, Rep. | COG | 2013 | 2.203900e+05 |
| 1042 | Congo, Rep. | COG | 2012 | 2.205100e+05 |
| 1043 | Congo, Rep. | COG | 2011 | 2.206300e+05 |
| 1044 | Congo, Rep. | COG | 2010 | 2.207500e+05 |
| 1045 | Costa Rica | CRI | 2020 | 3.034870e+04 |
| 1046 | Costa Rica | CRI | 2019 | 3.018500e+04 |
| 1047 | Costa Rica | CRI | 2018 | 3.002130e+04 |
| 1048 | Costa Rica | CRI | 2017 | 2.985770e+04 |
| 1049 | Costa Rica | CRI | 2016 | 2.969400e+04 |
| 1050 | Costa Rica | CRI | 2015 | 2.953030e+04 |
| 1051 | Costa Rica | CRI | 2014 | 2.936664e+04 |
| 1052 | Costa Rica | CRI | 2013 | 2.920298e+04 |
| 1053 | Costa Rica | CRI | 2012 | 2.903932e+04 |
| 1054 | Costa Rica | CRI | 2011 | 2.887566e+04 |
| 1055 | Costa Rica | CRI | 2010 | 2.871200e+04 |
| 1056 | Cote d'Ivoire | CIV | 2020 | 2.836710e+04 |
| 1057 | Cote d'Ivoire | CIV | 2019 | 2.949600e+04 |
| 1058 | Cote d'Ivoire | CIV | 2018 | 3.062480e+04 |
| 1059 | Cote d'Ivoire | CIV | 2017 | 3.175370e+04 |
| 1060 | Cote d'Ivoire | CIV | 2016 | 3.288260e+04 |
| 1061 | Cote d'Ivoire | CIV | 2015 | 3.401150e+04 |
| 1062 | Cote d'Ivoire | CIV | 2014 | 3.514036e+04 |
| 1063 | Cote d'Ivoire | CIV | 2013 | 3.626922e+04 |
| 1064 | Cote d'Ivoire | CIV | 2012 | 3.739808e+04 |
| 1065 | Cote d'Ivoire | CIV | 2011 | 3.852694e+04 |
| 1066 | Cote d'Ivoire | CIV | 2010 | 3.965580e+04 |
| 1067 | Croatia | HRV | 2020 | 1.939110e+04 |
| 1068 | Croatia | HRV | 2019 | 1.936610e+04 |
| 1069 | Croatia | HRV | 2018 | 1.934110e+04 |
| 1070 | Croatia | HRV | 2017 | 1.931608e+04 |
| 1071 | Croatia | HRV | 2016 | 1.924120e+04 |
| 1072 | Croatia | HRV | 2015 | 1.922000e+04 |
| 1073 | Croatia | HRV | 2014 | 1.921600e+04 |
| 1074 | Croatia | HRV | 2013 | 1.921200e+04 |
| 1075 | Croatia | HRV | 2012 | 1.920800e+04 |
| 1076 | Croatia | HRV | 2011 | 1.920400e+04 |
| 1077 | Croatia | HRV | 2010 | 1.920000e+04 |
| 1078 | Cuba | CUB | 2020 | 3.242000e+04 |
| 1079 | Cuba | CUB | 2019 | 3.242000e+04 |
| 1080 | Cuba | CUB | 2018 | 3.242000e+04 |
| 1081 | Cuba | CUB | 2017 | 3.242000e+04 |
| 1082 | Cuba | CUB | 2016 | 3.241000e+04 |
| 1083 | Cuba | CUB | 2015 | 3.184000e+04 |
| 1084 | Cuba | CUB | 2014 | 3.133600e+04 |
| 1085 | Cuba | CUB | 2013 | 3.083200e+04 |
| 1086 | Cuba | CUB | 2012 | 3.032800e+04 |
| 1087 | Cuba | CUB | 2011 | 2.982400e+04 |
| 1088 | Cuba | CUB | 2010 | 2.932000e+04 |
| 1089 | Curacao | CUW | 2020 | 7.000000e-01 |
| 1090 | Curacao | CUW | 2019 | 7.000000e-01 |
| 1091 | Curacao | CUW | 2018 | 7.000000e-01 |
| 1092 | Curacao | CUW | 2017 | 7.000000e-01 |
| 1093 | Curacao | CUW | 2016 | 7.000000e-01 |
| 1094 | Curacao | CUW | 2015 | 7.000000e-01 |
| 1095 | Curacao | CUW | 2014 | 7.000000e-01 |
| 1096 | Curacao | CUW | 2013 | 7.000000e-01 |
| 1097 | Curacao | CUW | 2012 | 7.000000e-01 |
| 1098 | Curacao | CUW | 2011 | 7.000000e-01 |
| 1099 | Curacao | CUW | 2010 | NaN |
| 1100 | Cyprus | CYP | 2020 | 1.725300e+03 |
| 1101 | Cyprus | CYP | 2019 | 1.725500e+03 |
| 1102 | Cyprus | CYP | 2018 | 1.725700e+03 |
| 1103 | Cyprus | CYP | 2017 | 1.725900e+03 |
| 1104 | Cyprus | CYP | 2016 | 1.726100e+03 |
| 1105 | Cyprus | CYP | 2015 | 1.727100e+03 |
| 1106 | Cyprus | CYP | 2014 | 1.727360e+03 |
| 1107 | Cyprus | CYP | 2013 | 1.727620e+03 |
| 1108 | Cyprus | CYP | 2012 | 1.727880e+03 |
| 1109 | Cyprus | CYP | 2011 | 1.728140e+03 |
| 1110 | Cyprus | CYP | 2010 | 1.728400e+03 |
| 1111 | Czechia | CZE | 2020 | 2.677090e+04 |
| 1112 | Czechia | CZE | 2019 | 2.675280e+04 |
| 1113 | Czechia | CZE | 2018 | 2.673470e+04 |
| 1114 | Czechia | CZE | 2017 | 2.671660e+04 |
| 1115 | Czechia | CZE | 2016 | 2.669850e+04 |
| 1116 | Czechia | CZE | 2015 | 2.668390e+04 |
| 1117 | Czechia | CZE | 2014 | 2.666188e+04 |
| 1118 | Czechia | CZE | 2013 | 2.663986e+04 |
| 1119 | Czechia | CZE | 2012 | 2.661784e+04 |
| 1120 | Czechia | CZE | 2011 | 2.659582e+04 |
| 1121 | Czechia | CZE | 2010 | 2.657380e+04 |
| 1122 | Denmark | DNK | 2020 | 6.284400e+03 |
| 1123 | Denmark | DNK | 2019 | 6.275000e+03 |
| 1124 | Denmark | DNK | 2018 | 6.265600e+03 |
| 1125 | Denmark | DNK | 2017 | 6.256000e+03 |
| 1126 | Denmark | DNK | 2016 | 6.246600e+03 |
| 1127 | Denmark | DNK | 2015 | 6.246800e+03 |
| 1128 | Denmark | DNK | 2014 | 6.170420e+03 |
| 1129 | Denmark | DNK | 2013 | 6.094040e+03 |
| 1130 | Denmark | DNK | 2012 | 6.017660e+03 |
| 1131 | Denmark | DNK | 2011 | 5.941280e+03 |
| 1132 | Denmark | DNK | 2010 | 5.864900e+03 |
| 1133 | Djibouti | DJI | 2020 | 5.800000e+01 |
| 1134 | Djibouti | DJI | 2019 | 5.700000e+01 |
| 1135 | Djibouti | DJI | 2018 | 5.640000e+01 |
| 1136 | Djibouti | DJI | 2017 | 5.610000e+01 |
| 1137 | Djibouti | DJI | 2016 | 5.600000e+01 |
| 1138 | Djibouti | DJI | 2015 | 5.600000e+01 |
| 1139 | Djibouti | DJI | 2014 | 5.600000e+01 |
| 1140 | Djibouti | DJI | 2013 | 5.600000e+01 |
| 1141 | Djibouti | DJI | 2012 | 5.600000e+01 |
| 1142 | Djibouti | DJI | 2011 | 5.600000e+01 |
| 1143 | Djibouti | DJI | 2010 | 5.600000e+01 |
| 1144 | Dominica | DMA | 2020 | 4.787000e+02 |
| 1145 | Dominica | DMA | 2019 | 4.787000e+02 |
| 1146 | Dominica | DMA | 2018 | 4.787000e+02 |
| 1147 | Dominica | DMA | 2017 | 4.787000e+02 |
| 1148 | Dominica | DMA | 2016 | 4.787000e+02 |
| 1149 | Dominica | DMA | 2015 | 4.787000e+02 |
| 1150 | Dominica | DMA | 2014 | 4.787000e+02 |
| 1151 | Dominica | DMA | 2013 | 4.787000e+02 |
| 1152 | Dominica | DMA | 2012 | 4.787000e+02 |
| 1153 | Dominica | DMA | 2011 | 4.787000e+02 |
| 1154 | Dominica | DMA | 2010 | 4.787000e+02 |
| 1155 | Dominican Republic | DOM | 2020 | 2.144100e+04 |
| 1156 | Dominican Republic | DOM | 2019 | 2.136010e+04 |
| 1157 | Dominican Republic | DOM | 2018 | 2.127920e+04 |
| 1158 | Dominican Republic | DOM | 2017 | 2.119830e+04 |
| 1159 | Dominican Republic | DOM | 2016 | 2.111740e+04 |
| 1160 | Dominican Republic | DOM | 2015 | 2.103650e+04 |
| 1161 | Dominican Republic | DOM | 2014 | 2.097544e+04 |
| 1162 | Dominican Republic | DOM | 2013 | 2.091438e+04 |
| 1163 | Dominican Republic | DOM | 2012 | 2.085332e+04 |
| 1164 | Dominican Republic | DOM | 2011 | 2.079226e+04 |
| 1165 | Dominican Republic | DOM | 2010 | 2.073120e+04 |
| 1166 | Ecuador | ECU | 2020 | 1.249783e+05 |
| 1167 | Ecuador | ECU | 2019 | 1.256210e+05 |
| 1168 | Ecuador | ECU | 2018 | 1.262637e+05 |
| 1169 | Ecuador | ECU | 2017 | 1.269064e+05 |
| 1170 | Ecuador | ECU | 2016 | 1.275491e+05 |
| 1171 | Ecuador | ECU | 2015 | 1.281918e+05 |
| 1172 | Ecuador | ECU | 2014 | 1.286098e+05 |
| 1173 | Ecuador | ECU | 2013 | 1.290278e+05 |
| 1174 | Ecuador | ECU | 2012 | 1.294459e+05 |
| 1175 | Ecuador | ECU | 2011 | 1.298639e+05 |
| 1176 | Ecuador | ECU | 2010 | 1.302819e+05 |
| 1177 | Egypt, Arab Rep. | EGY | 2020 | 4.498000e+02 |
| 1178 | Egypt, Arab Rep. | EGY | 2019 | 4.498000e+02 |
| 1179 | Egypt, Arab Rep. | EGY | 2018 | 4.498000e+02 |
| 1180 | Egypt, Arab Rep. | EGY | 2017 | 4.498000e+02 |
| 1181 | Egypt, Arab Rep. | EGY | 2016 | 4.498000e+02 |
| 1182 | Egypt, Arab Rep. | EGY | 2015 | 4.842000e+02 |
| 1183 | Egypt, Arab Rep. | EGY | 2014 | 5.186400e+02 |
| 1184 | Egypt, Arab Rep. | EGY | 2013 | 5.530800e+02 |
| 1185 | Egypt, Arab Rep. | EGY | 2012 | 5.875200e+02 |
| 1186 | Egypt, Arab Rep. | EGY | 2011 | 6.219600e+02 |
| 1187 | Egypt, Arab Rep. | EGY | 2010 | 6.564000e+02 |
| 1188 | El Salvador | SLV | 2020 | 5.838800e+03 |
| 1189 | El Salvador | SLV | 2019 | 5.883800e+03 |
| 1190 | El Salvador | SLV | 2018 | 5.928800e+03 |
| 1191 | El Salvador | SLV | 2017 | 5.973800e+03 |
| 1192 | El Salvador | SLV | 2016 | 6.018800e+03 |
| 1193 | El Salvador | SLV | 2015 | 6.063800e+03 |
| 1194 | El Salvador | SLV | 2014 | 6.108800e+03 |
| 1195 | El Salvador | SLV | 2013 | 6.153800e+03 |
| 1196 | El Salvador | SLV | 2012 | 6.198800e+03 |
| 1197 | El Salvador | SLV | 2011 | 6.243800e+03 |
| 1198 | El Salvador | SLV | 2010 | 6.288800e+03 |
| 1199 | Equatorial Guinea | GNQ | 2020 | 2.448420e+04 |
| 1200 | Equatorial Guinea | GNQ | 2019 | 2.456780e+04 |
| 1201 | Equatorial Guinea | GNQ | 2018 | 2.465140e+04 |
| 1202 | Equatorial Guinea | GNQ | 2017 | 2.473500e+04 |
| 1203 | Equatorial Guinea | GNQ | 2016 | 2.481860e+04 |
| 1204 | Equatorial Guinea | GNQ | 2015 | 2.490220e+04 |
| 1205 | Equatorial Guinea | GNQ | 2014 | 2.498578e+04 |
| 1206 | Equatorial Guinea | GNQ | 2013 | 2.506936e+04 |
| 1207 | Equatorial Guinea | GNQ | 2012 | 2.515294e+04 |
| 1208 | Equatorial Guinea | GNQ | 2011 | 2.523652e+04 |
| 1209 | Equatorial Guinea | GNQ | 2010 | 2.532010e+04 |
| 1210 | Eritrea | ERI | 2020 | 1.055260e+04 |
| 1211 | Eritrea | ERI | 2019 | 1.058420e+04 |
| 1212 | Eritrea | ERI | 2018 | 1.061580e+04 |
| 1213 | Eritrea | ERI | 2017 | 1.064740e+04 |
| 1214 | Eritrea | ERI | 2016 | 1.067900e+04 |
| 1215 | Eritrea | ERI | 2015 | 1.071060e+04 |
| 1216 | Eritrea | ERI | 2014 | 1.074220e+04 |
| 1217 | Eritrea | ERI | 2013 | 1.077380e+04 |
| 1218 | Eritrea | ERI | 2012 | 1.080540e+04 |
| 1219 | Eritrea | ERI | 2011 | 1.083700e+04 |
| 1220 | Eritrea | ERI | 2010 | 1.086860e+04 |
| 1221 | Estonia | EST | 2020 | 2.438400e+04 |
| 1222 | Estonia | EST | 2019 | 2.438400e+04 |
| 1223 | Estonia | EST | 2018 | 2.438400e+04 |
| 1224 | Estonia | EST | 2017 | 2.438400e+04 |
| 1225 | Estonia | EST | 2016 | 2.421250e+04 |
| 1226 | Estonia | EST | 2015 | 2.421010e+04 |
| 1227 | Estonia | EST | 2014 | 2.404012e+04 |
| 1228 | Estonia | EST | 2013 | 2.387014e+04 |
| 1229 | Estonia | EST | 2012 | 2.370016e+04 |
| 1230 | Estonia | EST | 2011 | 2.353018e+04 |
| 1231 | Estonia | EST | 2010 | 2.336020e+04 |
| 1232 | Eswatini | SWZ | 2020 | 4.975600e+03 |
| 1233 | Eswatini | SWZ | 2019 | 4.963500e+03 |
| 1234 | Eswatini | SWZ | 2018 | 4.951400e+03 |
| 1235 | Eswatini | SWZ | 2017 | 4.939300e+03 |
| 1236 | Eswatini | SWZ | 2016 | 4.927200e+03 |
| 1237 | Eswatini | SWZ | 2015 | 4.915000e+03 |
| 1238 | Eswatini | SWZ | 2014 | 4.902860e+03 |
| 1239 | Eswatini | SWZ | 2013 | 4.890720e+03 |
| 1240 | Eswatini | SWZ | 2012 | 4.878580e+03 |
| 1241 | Eswatini | SWZ | 2011 | 4.866440e+03 |
| 1242 | Eswatini | SWZ | 2010 | 4.854300e+03 |
| 1243 | Ethiopia | ETH | 2020 | 1.706850e+05 |
| 1244 | Ethiopia | ETH | 2019 | 1.714150e+05 |
| 1245 | Ethiopia | ETH | 2018 | 1.721450e+05 |
| 1246 | Ethiopia | ETH | 2017 | 1.728750e+05 |
| 1247 | Ethiopia | ETH | 2016 | 1.736050e+05 |
| 1248 | Ethiopia | ETH | 2015 | 1.743350e+05 |
| 1249 | Ethiopia | ETH | 2014 | 1.750650e+05 |
| 1250 | Ethiopia | ETH | 2013 | 1.757950e+05 |
| 1251 | Ethiopia | ETH | 2012 | 1.765250e+05 |
| 1252 | Ethiopia | ETH | 2011 | 1.772550e+05 |
| 1253 | Ethiopia | ETH | 2010 | 1.779850e+05 |
| 1254 | Faroe Islands | FRO | 2020 | 8.000000e-01 |
| 1255 | Faroe Islands | FRO | 2019 | 8.000000e-01 |
| 1256 | Faroe Islands | FRO | 2018 | 8.000000e-01 |
| 1257 | Faroe Islands | FRO | 2017 | 8.000000e-01 |
| 1258 | Faroe Islands | FRO | 2016 | 8.000000e-01 |
| 1259 | Faroe Islands | FRO | 2015 | 8.000000e-01 |
| 1260 | Faroe Islands | FRO | 2014 | 8.000000e-01 |
| 1261 | Faroe Islands | FRO | 2013 | 8.000000e-01 |
| 1262 | Faroe Islands | FRO | 2012 | 8.000000e-01 |
| 1263 | Faroe Islands | FRO | 2011 | 8.000000e-01 |
| 1264 | Faroe Islands | FRO | 2010 | 8.000000e-01 |
| 1265 | Fiji | FJI | 2020 | 1.140020e+04 |
| 1266 | Fiji | FJI | 2019 | 1.133340e+04 |
| 1267 | Fiji | FJI | 2018 | 1.126660e+04 |
| 1268 | Fiji | FJI | 2017 | 1.119980e+04 |
| 1269 | Fiji | FJI | 2016 | 1.113300e+04 |
| 1270 | Fiji | FJI | 2015 | 1.106620e+04 |
| 1271 | Fiji | FJI | 2014 | 1.099944e+04 |
| 1272 | Fiji | FJI | 2013 | 1.093268e+04 |
| 1273 | Fiji | FJI | 2012 | 1.086592e+04 |
| 1274 | Fiji | FJI | 2011 | 1.079916e+04 |
| 1275 | Fiji | FJI | 2010 | 1.073240e+04 |
| 1276 | Finland | FIN | 2020 | 2.240900e+05 |
| 1277 | Finland | FIN | 2019 | 2.240900e+05 |
| 1278 | Finland | FIN | 2018 | 2.240900e+05 |
| 1279 | Finland | FIN | 2017 | 2.240900e+05 |
| 1280 | Finland | FIN | 2016 | 2.240900e+05 |
| 1281 | Finland | FIN | 2015 | 2.240900e+05 |
| 1282 | Finland | FIN | 2014 | 2.237560e+05 |
| 1283 | Finland | FIN | 2013 | 2.234220e+05 |
| 1284 | Finland | FIN | 2012 | 2.230880e+05 |
| 1285 | Finland | FIN | 2011 | 2.227540e+05 |
| 1286 | Finland | FIN | 2010 | 2.224200e+05 |
| 1287 | France | FRA | 2020 | 1.725300e+05 |
| 1288 | France | FRA | 2019 | 1.716960e+05 |
| 1289 | France | FRA | 2018 | 1.708620e+05 |
| 1290 | France | FRA | 2017 | 1.700280e+05 |
| 1291 | France | FRA | 2016 | 1.691940e+05 |
| 1292 | France | FRA | 2015 | 1.683600e+05 |
| 1293 | France | FRA | 2014 | 1.675260e+05 |
| 1294 | France | FRA | 2013 | 1.666920e+05 |
| 1295 | France | FRA | 2012 | 1.658580e+05 |
| 1296 | France | FRA | 2011 | 1.650240e+05 |
| 1297 | France | FRA | 2010 | 1.641900e+05 |
| 1298 | French Polynesia | PYF | 2020 | 1.494600e+03 |
| 1299 | French Polynesia | PYF | 2019 | 1.494600e+03 |
| 1300 | French Polynesia | PYF | 2018 | 1.494600e+03 |
| 1301 | French Polynesia | PYF | 2017 | 1.494600e+03 |
| 1302 | French Polynesia | PYF | 2016 | 1.494600e+03 |
| 1303 | French Polynesia | PYF | 2015 | 1.494600e+03 |
| 1304 | French Polynesia | PYF | 2014 | 1.494600e+03 |
| 1305 | French Polynesia | PYF | 2013 | 1.494600e+03 |
| 1306 | French Polynesia | PYF | 2012 | 1.494600e+03 |
| 1307 | French Polynesia | PYF | 2011 | 1.494600e+03 |
| 1308 | French Polynesia | PYF | 2010 | 1.494600e+03 |
| 1309 | Gabon | GAB | 2020 | 2.353060e+05 |
| 1310 | Gabon | GAB | 2019 | 2.354248e+05 |
| 1311 | Gabon | GAB | 2018 | 2.355436e+05 |
| 1312 | Gabon | GAB | 2017 | 2.356624e+05 |
| 1313 | Gabon | GAB | 2016 | 2.357812e+05 |
| 1314 | Gabon | GAB | 2015 | 2.359000e+05 |
| 1315 | Gabon | GAB | 2014 | 2.360188e+05 |
| 1316 | Gabon | GAB | 2013 | 2.361376e+05 |
| 1317 | Gabon | GAB | 2012 | 2.362565e+05 |
| 1318 | Gabon | GAB | 2011 | 2.363753e+05 |
| 1319 | Gabon | GAB | 2010 | 2.364941e+05 |
| 1320 | Gambia, The | GMB | 2020 | 2.426700e+03 |
| 1321 | Gambia, The | GMB | 2019 | 2.484000e+03 |
| 1322 | Gambia, The | GMB | 2018 | 2.541400e+03 |
| 1323 | Gambia, The | GMB | 2017 | 2.598700e+03 |
| 1324 | Gambia, The | GMB | 2016 | 2.656000e+03 |
| 1325 | Gambia, The | GMB | 2015 | 2.713400e+03 |
| 1326 | Gambia, The | GMB | 2014 | 2.770720e+03 |
| 1327 | Gambia, The | GMB | 2013 | 2.828040e+03 |
| 1328 | Gambia, The | GMB | 2012 | 2.885360e+03 |
| 1329 | Gambia, The | GMB | 2011 | 2.942680e+03 |
| 1330 | Gambia, The | GMB | 2010 | 3.000000e+03 |
| 1331 | Georgia | GEO | 2020 | 2.822400e+04 |
| 1332 | Georgia | GEO | 2019 | 2.822400e+04 |
| 1333 | Georgia | GEO | 2018 | 2.822400e+04 |
| 1334 | Georgia | GEO | 2017 | 2.822400e+04 |
| 1335 | Georgia | GEO | 2016 | 2.822400e+04 |
| 1336 | Georgia | GEO | 2015 | 2.822400e+04 |
| 1337 | Georgia | GEO | 2014 | 2.822400e+04 |
| 1338 | Georgia | GEO | 2013 | 2.822400e+04 |
| 1339 | Georgia | GEO | 2012 | 2.822400e+04 |
| 1340 | Georgia | GEO | 2011 | 2.822400e+04 |
| 1341 | Georgia | GEO | 2010 | 2.822400e+04 |
| 1342 | Germany | DEU | 2020 | 1.141900e+05 |
| 1343 | Germany | DEU | 2019 | 1.141900e+05 |
| 1344 | Germany | DEU | 2018 | 1.141900e+05 |
| 1345 | Germany | DEU | 2017 | 1.141900e+05 |
| 1346 | Germany | DEU | 2016 | 1.141900e+05 |
| 1347 | Germany | DEU | 2015 | 1.141900e+05 |
| 1348 | Germany | DEU | 2014 | 1.141700e+05 |
| 1349 | Germany | DEU | 2013 | 1.141500e+05 |
| 1350 | Germany | DEU | 2012 | 1.141300e+05 |
| 1351 | Germany | DEU | 2011 | 1.141100e+05 |
| 1352 | Germany | DEU | 2010 | 1.140900e+05 |
| 1353 | Ghana | GHA | 2020 | 7.985710e+04 |
| 1354 | Ghana | GHA | 2019 | 7.978480e+04 |
| 1355 | Ghana | GHA | 2018 | 7.971260e+04 |
| 1356 | Ghana | GHA | 2017 | 7.964040e+04 |
| 1357 | Ghana | GHA | 2016 | 7.922240e+04 |
| 1358 | Ghana | GHA | 2015 | 7.880440e+04 |
| 1359 | Ghana | GHA | 2014 | 7.892938e+04 |
| 1360 | Ghana | GHA | 2013 | 7.905436e+04 |
| 1361 | Ghana | GHA | 2012 | 7.917934e+04 |
| 1362 | Ghana | GHA | 2011 | 7.930432e+04 |
| 1363 | Ghana | GHA | 2010 | 7.942930e+04 |
| 1364 | Gibraltar | GIB | 2020 | 0.000000e+00 |
| 1365 | Gibraltar | GIB | 2019 | 0.000000e+00 |
| 1366 | Gibraltar | GIB | 2018 | 0.000000e+00 |
| 1367 | Gibraltar | GIB | 2017 | 0.000000e+00 |
| 1368 | Gibraltar | GIB | 2016 | 0.000000e+00 |
| 1369 | Gibraltar | GIB | 2015 | 0.000000e+00 |
| 1370 | Gibraltar | GIB | 2014 | 0.000000e+00 |
| 1371 | Gibraltar | GIB | 2013 | 0.000000e+00 |
| 1372 | Gibraltar | GIB | 2012 | 0.000000e+00 |
| 1373 | Gibraltar | GIB | 2011 | 0.000000e+00 |
| 1374 | Gibraltar | GIB | 2010 | 0.000000e+00 |
| 1375 | Greece | GRC | 2020 | 3.901800e+04 |
| 1376 | Greece | GRC | 2019 | 3.901800e+04 |
| 1377 | Greece | GRC | 2018 | 3.901800e+04 |
| 1378 | Greece | GRC | 2017 | 3.901800e+04 |
| 1379 | Greece | GRC | 2016 | 3.901800e+04 |
| 1380 | Greece | GRC | 2015 | 3.901803e+04 |
| 1381 | Greece | GRC | 2014 | 3.901803e+04 |
| 1382 | Greece | GRC | 2013 | 3.901803e+04 |
| 1383 | Greece | GRC | 2012 | 3.901803e+04 |
| 1384 | Greece | GRC | 2011 | 3.901803e+04 |
| 1385 | Greece | GRC | 2010 | 3.901803e+04 |
| 1386 | Greenland | GRL | 2020 | 2.200000e+00 |
| 1387 | Greenland | GRL | 2019 | 2.200000e+00 |
| 1388 | Greenland | GRL | 2018 | 2.200000e+00 |
| 1389 | Greenland | GRL | 2017 | 2.200000e+00 |
| 1390 | Greenland | GRL | 2016 | 2.200000e+00 |
| 1391 | Greenland | GRL | 2015 | 2.200000e+00 |
| 1392 | Greenland | GRL | 2014 | 2.200000e+00 |
| 1393 | Greenland | GRL | 2013 | 2.200000e+00 |
| 1394 | Greenland | GRL | 2012 | 2.200000e+00 |
| 1395 | Greenland | GRL | 2011 | 2.200000e+00 |
| 1396 | Greenland | GRL | 2010 | 2.200000e+00 |
| 1397 | Grenada | GRD | 2020 | 1.770000e+02 |
| 1398 | Grenada | GRD | 2019 | 1.770000e+02 |
| 1399 | Grenada | GRD | 2018 | 1.770000e+02 |
| 1400 | Grenada | GRD | 2017 | 1.770000e+02 |
| 1401 | Grenada | GRD | 2016 | 1.770000e+02 |
| 1402 | Grenada | GRD | 2015 | 1.770000e+02 |
| 1403 | Grenada | GRD | 2014 | 1.770000e+02 |
| 1404 | Grenada | GRD | 2013 | 1.770000e+02 |
| 1405 | Grenada | GRD | 2012 | 1.770000e+02 |
| 1406 | Grenada | GRD | 2011 | 1.770000e+02 |
| 1407 | Grenada | GRD | 2010 | 1.770000e+02 |
| 1408 | Guam | GUM | 2020 | 2.800000e+02 |
| 1409 | Guam | GUM | 2019 | 2.800000e+02 |
| 1410 | Guam | GUM | 2018 | 2.800000e+02 |
| 1411 | Guam | GUM | 2017 | 2.800000e+02 |
| 1412 | Guam | GUM | 2016 | 2.800000e+02 |
| 1413 | Guam | GUM | 2015 | 2.500000e+02 |
| 1414 | Guam | GUM | 2014 | 2.480000e+02 |
| 1415 | Guam | GUM | 2013 | 2.460000e+02 |
| 1416 | Guam | GUM | 2012 | 2.440000e+02 |
| 1417 | Guam | GUM | 2011 | 2.420000e+02 |
| 1418 | Guam | GUM | 2010 | 2.400000e+02 |
| 1419 | Guatemala | GTM | 2020 | 3.527800e+04 |
| 1420 | Guatemala | GTM | 2019 | 3.539400e+04 |
| 1421 | Guatemala | GTM | 2018 | 3.551000e+04 |
| 1422 | Guatemala | GTM | 2017 | 3.562600e+04 |
| 1423 | Guatemala | GTM | 2016 | 3.574200e+04 |
| 1424 | Guatemala | GTM | 2015 | 3.585800e+04 |
| 1425 | Guatemala | GTM | 2014 | 3.613160e+04 |
| 1426 | Guatemala | GTM | 2013 | 3.640520e+04 |
| 1427 | Guatemala | GTM | 2012 | 3.667880e+04 |
| 1428 | Guatemala | GTM | 2011 | 3.695240e+04 |
| 1429 | Guatemala | GTM | 2010 | 3.722600e+04 |
| 1430 | Guinea | GIN | 2020 | 6.189000e+04 |
| 1431 | Guinea | GIN | 2019 | 6.229000e+04 |
| 1432 | Guinea | GIN | 2018 | 6.269000e+04 |
| 1433 | Guinea | GIN | 2017 | 6.309000e+04 |
| 1434 | Guinea | GIN | 2016 | 6.349000e+04 |
| 1435 | Guinea | GIN | 2015 | 6.389000e+04 |
| 1436 | Guinea | GIN | 2014 | 6.425000e+04 |
| 1437 | Guinea | GIN | 2013 | 6.461000e+04 |
| 1438 | Guinea | GIN | 2012 | 6.497000e+04 |
| 1439 | Guinea | GIN | 2011 | 6.533000e+04 |
| 1440 | Guinea | GIN | 2010 | 6.569000e+04 |
| 1441 | Guinea-Bissau | GNB | 2020 | 1.980010e+04 |
| 1442 | Guinea-Bissau | GNB | 2019 | 1.988450e+04 |
| 1443 | Guinea-Bissau | GNB | 2018 | 1.996890e+04 |
| 1444 | Guinea-Bissau | GNB | 2017 | 2.005330e+04 |
| 1445 | Guinea-Bissau | GNB | 2016 | 2.013770e+04 |
| 1446 | Guinea-Bissau | GNB | 2015 | 2.022210e+04 |
| 1447 | Guinea-Bissau | GNB | 2014 | 2.030654e+04 |
| 1448 | Guinea-Bissau | GNB | 2013 | 2.039098e+04 |
| 1449 | Guinea-Bissau | GNB | 2012 | 2.047542e+04 |
| 1450 | Guinea-Bissau | GNB | 2011 | 2.055986e+04 |
| 1451 | Guinea-Bissau | GNB | 2010 | 2.064430e+04 |
| 1452 | Guyana | GUY | 2020 | 1.841534e+05 |
| 1453 | Guyana | GUY | 2019 | 1.842454e+05 |
| 1454 | Guyana | GUY | 2018 | 1.843375e+05 |
| 1455 | Guyana | GUY | 2017 | 1.844295e+05 |
| 1456 | Guyana | GUY | 2016 | 1.845216e+05 |
| 1457 | Guyana | GUY | 2015 | 1.846136e+05 |
| 1458 | Guyana | GUY | 2014 | 1.847305e+05 |
| 1459 | Guyana | GUY | 2013 | 1.848474e+05 |
| 1460 | Guyana | GUY | 2012 | 1.849643e+05 |
| 1461 | Guyana | GUY | 2011 | 1.850812e+05 |
| 1462 | Guyana | GUY | 2010 | 1.851981e+05 |
| 1463 | Haiti | HTI | 2020 | 3.473000e+03 |
| 1464 | Haiti | HTI | 2019 | 3.504100e+03 |
| 1465 | Haiti | HTI | 2018 | 3.535200e+03 |
| 1466 | Haiti | HTI | 2017 | 3.566300e+03 |
| 1467 | Haiti | HTI | 2016 | 3.597400e+03 |
| 1468 | Haiti | HTI | 2015 | 3.628500e+03 |
| 1469 | Haiti | HTI | 2014 | 3.659560e+03 |
| 1470 | Haiti | HTI | 2013 | 3.690620e+03 |
| 1471 | Haiti | HTI | 2012 | 3.721680e+03 |
| 1472 | Haiti | HTI | 2011 | 3.752740e+03 |
| 1473 | Haiti | HTI | 2010 | 3.783800e+03 |
| 1474 | Honduras | HND | 2020 | 6.359260e+04 |
| 1475 | Honduras | HND | 2019 | 6.380210e+04 |
| 1476 | Honduras | HND | 2018 | 6.401160e+04 |
| 1477 | Honduras | HND | 2017 | 6.422110e+04 |
| 1478 | Honduras | HND | 2016 | 6.443050e+04 |
| 1479 | Honduras | HND | 2015 | 6.463830e+04 |
| 1480 | Honduras | HND | 2014 | 6.486158e+04 |
| 1481 | Honduras | HND | 2013 | 6.508486e+04 |
| 1482 | Honduras | HND | 2012 | 6.530814e+04 |
| 1483 | Honduras | HND | 2011 | 6.553142e+04 |
| 1484 | Honduras | HND | 2010 | 6.575470e+04 |
| 1485 | Hong Kong SAR, China | HKG | 2020 | NaN |
| 1486 | Hong Kong SAR, China | HKG | 2019 | NaN |
| 1487 | Hong Kong SAR, China | HKG | 2018 | NaN |
| 1488 | Hong Kong SAR, China | HKG | 2017 | NaN |
| 1489 | Hong Kong SAR, China | HKG | 2016 | NaN |
| 1490 | Hong Kong SAR, China | HKG | 2015 | NaN |
| 1491 | Hong Kong SAR, China | HKG | 2014 | NaN |
| 1492 | Hong Kong SAR, China | HKG | 2013 | NaN |
| 1493 | Hong Kong SAR, China | HKG | 2012 | NaN |
| 1494 | Hong Kong SAR, China | HKG | 2011 | NaN |
| 1495 | Hong Kong SAR, China | HKG | 2010 | NaN |
| 1496 | Hungary | HUN | 2020 | 2.053010e+04 |
| 1497 | Hungary | HUN | 2019 | 2.054470e+04 |
| 1498 | Hungary | HUN | 2018 | 2.055920e+04 |
| 1499 | Hungary | HUN | 2017 | 2.057270e+04 |
| 1500 | Hungary | HUN | 2016 | 2.058730e+04 |
| 1501 | Hungary | HUN | 2015 | 2.060820e+04 |
| 1502 | Hungary | HUN | 2014 | 2.057934e+04 |
| 1503 | Hungary | HUN | 2013 | 2.055048e+04 |
| 1504 | Hungary | HUN | 2012 | 2.052162e+04 |
| 1505 | Hungary | HUN | 2011 | 2.049276e+04 |
| 1506 | Hungary | HUN | 2010 | 2.046390e+04 |
| 1507 | Iceland | ISL | 2020 | 5.135000e+02 |
| 1508 | Iceland | ISL | 2019 | 5.069000e+02 |
| 1509 | Iceland | ISL | 2018 | 5.004000e+02 |
| 1510 | Iceland | ISL | 2017 | 4.938000e+02 |
| 1511 | Iceland | ISL | 2016 | 4.866000e+02 |
| 1512 | Iceland | ISL | 2015 | 4.816000e+02 |
| 1513 | Iceland | ISL | 2014 | 4.746200e+02 |
| 1514 | Iceland | ISL | 2013 | 4.676400e+02 |
| 1515 | Iceland | ISL | 2012 | 4.606600e+02 |
| 1516 | Iceland | ISL | 2011 | 4.536800e+02 |
| 1517 | Iceland | ISL | 2010 | 4.467000e+02 |
| 1518 | India | IND | 2020 | 7.216000e+05 |
| 1519 | India | IND | 2019 | 7.189360e+05 |
| 1520 | India | IND | 2018 | 7.162720e+05 |
| 1521 | India | IND | 2017 | 7.136080e+05 |
| 1522 | India | IND | 2016 | 7.109440e+05 |
| 1523 | India | IND | 2015 | 7.082800e+05 |
| 1524 | India | IND | 2014 | 7.056160e+05 |
| 1525 | India | IND | 2013 | 7.029520e+05 |
| 1526 | India | IND | 2012 | 7.002880e+05 |
| 1527 | India | IND | 2011 | 6.976240e+05 |
| 1528 | India | IND | 2010 | 6.949600e+05 |
| 1529 | Indonesia | IDN | 2020 | 9.213320e+05 |
| 1530 | Indonesia | IDN | 2019 | 9.273873e+05 |
| 1531 | Indonesia | IDN | 2018 | 9.334427e+05 |
| 1532 | Indonesia | IDN | 2017 | 9.394980e+05 |
| 1533 | Indonesia | IDN | 2016 | 9.527180e+05 |
| 1534 | Indonesia | IDN | 2015 | 9.502790e+05 |
| 1535 | Indonesia | IDN | 2014 | 9.595416e+05 |
| 1536 | Indonesia | IDN | 2013 | 9.688042e+05 |
| 1537 | Indonesia | IDN | 2012 | 9.780668e+05 |
| 1538 | Indonesia | IDN | 2011 | 9.873294e+05 |
| 1539 | Indonesia | IDN | 2010 | 9.965920e+05 |
| 1540 | Iran, Islamic Rep. | IRN | 2020 | 1.075187e+05 |
| 1541 | Iran, Islamic Rep. | IRN | 2019 | 1.074347e+05 |
| 1542 | Iran, Islamic Rep. | IRN | 2018 | 1.072703e+05 |
| 1543 | Iran, Islamic Rep. | IRN | 2017 | 1.071059e+05 |
| 1544 | Iran, Islamic Rep. | IRN | 2016 | 1.070208e+05 |
| 1545 | Iran, Islamic Rep. | IRN | 2015 | 1.069198e+05 |
| 1546 | Iran, Islamic Rep. | IRN | 2014 | 1.069198e+05 |
| 1547 | Iran, Islamic Rep. | IRN | 2013 | 1.069198e+05 |
| 1548 | Iran, Islamic Rep. | IRN | 2012 | 1.069198e+05 |
| 1549 | Iran, Islamic Rep. | IRN | 2011 | 1.069198e+05 |
| 1550 | Iran, Islamic Rep. | IRN | 2010 | 1.069198e+05 |
| 1551 | Iraq | IRQ | 2020 | 8.250000e+03 |
| 1552 | Iraq | IRQ | 2019 | 8.250000e+03 |
| 1553 | Iraq | IRQ | 2018 | 8.250000e+03 |
| 1554 | Iraq | IRQ | 2017 | 8.250000e+03 |
| 1555 | Iraq | IRQ | 2016 | 8.250000e+03 |
| 1556 | Iraq | IRQ | 2015 | 8.250000e+03 |
| 1557 | Iraq | IRQ | 2014 | 8.250000e+03 |
| 1558 | Iraq | IRQ | 2013 | 8.250000e+03 |
| 1559 | Iraq | IRQ | 2012 | 8.250000e+03 |
| 1560 | Iraq | IRQ | 2011 | 8.250000e+03 |
| 1561 | Iraq | IRQ | 2010 | 8.250000e+03 |
| 1562 | Ireland | IRL | 2020 | 7.820200e+03 |
| 1563 | Ireland | IRL | 2019 | 7.780200e+03 |
| 1564 | Ireland | IRL | 2018 | 7.740200e+03 |
| 1565 | Ireland | IRL | 2017 | 7.700200e+03 |
| 1566 | Ireland | IRL | 2016 | 7.623500e+03 |
| 1567 | Ireland | IRL | 2015 | 7.546700e+03 |
| 1568 | Ireland | IRL | 2014 | 7.478120e+03 |
| 1569 | Ireland | IRL | 2013 | 7.409540e+03 |
| 1570 | Ireland | IRL | 2012 | 7.340960e+03 |
| 1571 | Ireland | IRL | 2011 | 7.272380e+03 |
| 1572 | Ireland | IRL | 2010 | 7.203800e+03 |
| 1573 | Isle of Man | IMN | 2020 | 3.460000e+01 |
| 1574 | Isle of Man | IMN | 2019 | 3.460000e+01 |
| 1575 | Isle of Man | IMN | 2018 | 3.460000e+01 |
| 1576 | Isle of Man | IMN | 2017 | 3.460000e+01 |
| 1577 | Isle of Man | IMN | 2016 | 3.460000e+01 |
| 1578 | Isle of Man | IMN | 2015 | 3.460000e+01 |
| 1579 | Isle of Man | IMN | 2014 | 3.460000e+01 |
| 1580 | Isle of Man | IMN | 2013 | 3.460000e+01 |
| 1581 | Isle of Man | IMN | 2012 | 3.460000e+01 |
| 1582 | Isle of Man | IMN | 2011 | 3.460000e+01 |
| 1583 | Isle of Man | IMN | 2010 | 3.460000e+01 |
| 1584 | Israel | ISR | 2020 | 1.400000e+03 |
| 1585 | Israel | ISR | 2019 | 1.400000e+03 |
| 1586 | Israel | ISR | 2018 | 1.400000e+03 |
| 1587 | Israel | ISR | 2017 | 1.400000e+03 |
| 1588 | Israel | ISR | 2016 | 1.400000e+03 |
| 1589 | Israel | ISR | 2015 | 1.650000e+03 |
| 1590 | Israel | ISR | 2014 | 1.628000e+03 |
| 1591 | Israel | ISR | 2013 | 1.606000e+03 |
| 1592 | Israel | ISR | 2012 | 1.584000e+03 |
| 1593 | Israel | ISR | 2011 | 1.562000e+03 |
| 1594 | Israel | ISR | 2010 | 1.540000e+03 |
| 1595 | Italy | ITA | 2020 | 9.566130e+04 |
| 1596 | Italy | ITA | 2019 | 9.512320e+04 |
| 1597 | Italy | ITA | 2018 | 9.458510e+04 |
| 1598 | Italy | ITA | 2017 | 9.404700e+04 |
| 1599 | Italy | ITA | 2016 | 9.350890e+04 |
| 1600 | Italy | ITA | 2015 | 9.297080e+04 |
| 1601 | Italy | ITA | 2014 | 9.243272e+04 |
| 1602 | Italy | ITA | 2013 | 9.189464e+04 |
| 1603 | Italy | ITA | 2012 | 9.135656e+04 |
| 1604 | Italy | ITA | 2011 | 9.081848e+04 |
| 1605 | Italy | ITA | 2010 | 9.028040e+04 |
| 1606 | Jamaica | JAM | 2020 | 5.968900e+03 |
| 1607 | Jamaica | JAM | 2019 | 5.930000e+03 |
| 1608 | Jamaica | JAM | 2018 | 5.891200e+03 |
| 1609 | Jamaica | JAM | 2017 | 5.852300e+03 |
| 1610 | Jamaica | JAM | 2016 | 5.813400e+03 |
| 1611 | Jamaica | JAM | 2015 | 5.774600e+03 |
| 1612 | Jamaica | JAM | 2014 | 5.736580e+03 |
| 1613 | Jamaica | JAM | 2013 | 5.698560e+03 |
| 1614 | Jamaica | JAM | 2012 | 5.660540e+03 |
| 1615 | Jamaica | JAM | 2011 | 5.622520e+03 |
| 1616 | Jamaica | JAM | 2010 | 5.584500e+03 |
| 1617 | Japan | JPN | 2020 | 2.493500e+05 |
| 1618 | Japan | JPN | 2019 | 2.493500e+05 |
| 1619 | Japan | JPN | 2018 | 2.493500e+05 |
| 1620 | Japan | JPN | 2017 | 2.493500e+05 |
| 1621 | Japan | JPN | 2016 | 2.494000e+05 |
| 1622 | Japan | JPN | 2015 | 2.494400e+05 |
| 1623 | Japan | JPN | 2014 | 2.494840e+05 |
| 1624 | Japan | JPN | 2013 | 2.495280e+05 |
| 1625 | Japan | JPN | 2012 | 2.495720e+05 |
| 1626 | Japan | JPN | 2011 | 2.496160e+05 |
| 1627 | Japan | JPN | 2010 | 2.496600e+05 |
| 1628 | Jordan | JOR | 2020 | 9.750000e+02 |
| 1629 | Jordan | JOR | 2019 | 9.750000e+02 |
| 1630 | Jordan | JOR | 2018 | 9.750000e+02 |
| 1631 | Jordan | JOR | 2017 | 9.750000e+02 |
| 1632 | Jordan | JOR | 2016 | 9.750000e+02 |
| 1633 | Jordan | JOR | 2015 | 9.750000e+02 |
| 1634 | Jordan | JOR | 2014 | 9.750000e+02 |
| 1635 | Jordan | JOR | 2013 | 9.750000e+02 |
| 1636 | Jordan | JOR | 2012 | 9.750000e+02 |
| 1637 | Jordan | JOR | 2011 | 9.750000e+02 |
| 1638 | Jordan | JOR | 2010 | 9.750000e+02 |
| 1639 | Kazakhstan | KAZ | 2020 | 3.454680e+04 |
| 1640 | Kazakhstan | KAZ | 2019 | 3.425440e+04 |
| 1641 | Kazakhstan | KAZ | 2018 | 3.396201e+04 |
| 1642 | Kazakhstan | KAZ | 2017 | 3.366960e+04 |
| 1643 | Kazakhstan | KAZ | 2016 | 3.337710e+04 |
| 1644 | Kazakhstan | KAZ | 2015 | 3.308456e+04 |
| 1645 | Kazakhstan | KAZ | 2014 | 3.263201e+04 |
| 1646 | Kazakhstan | KAZ | 2013 | 3.217946e+04 |
| 1647 | Kazakhstan | KAZ | 2012 | 3.172690e+04 |
| 1648 | Kazakhstan | KAZ | 2011 | 3.127435e+04 |
| 1649 | Kazakhstan | KAZ | 2010 | 3.082179e+04 |
| 1650 | Kenya | KEN | 2020 | 3.611090e+04 |
| 1651 | Kenya | KEN | 2019 | 3.611090e+04 |
| 1652 | Kenya | KEN | 2018 | 3.611090e+04 |
| 1653 | Kenya | KEN | 2017 | 3.581530e+04 |
| 1654 | Kenya | KEN | 2016 | 3.551970e+04 |
| 1655 | Kenya | KEN | 2015 | 3.522410e+04 |
| 1656 | Kenya | KEN | 2014 | 3.541196e+04 |
| 1657 | Kenya | KEN | 2013 | 3.559982e+04 |
| 1658 | Kenya | KEN | 2012 | 3.578768e+04 |
| 1659 | Kenya | KEN | 2011 | 3.597554e+04 |
| 1660 | Kenya | KEN | 2010 | 3.616340e+04 |
| 1661 | Kiribati | KIR | 2020 | 1.180000e+01 |
| 1662 | Kiribati | KIR | 2019 | 1.180000e+01 |
| 1663 | Kiribati | KIR | 2018 | 1.180000e+01 |
| 1664 | Kiribati | KIR | 2017 | 1.180000e+01 |
| 1665 | Kiribati | KIR | 2016 | 1.180000e+01 |
| 1666 | Kiribati | KIR | 2015 | 1.180000e+01 |
| 1667 | Kiribati | KIR | 2014 | 1.180000e+01 |
| 1668 | Kiribati | KIR | 2013 | 1.180000e+01 |
| 1669 | Kiribati | KIR | 2012 | 1.180000e+01 |
| 1670 | Kiribati | KIR | 2011 | 1.180000e+01 |
| 1671 | Kiribati | KIR | 2010 | 1.180000e+01 |
| 1672 | Korea, Dem. People's Rep. | PRK | 2020 | 6.030090e+04 |
| 1673 | Korea, Dem. People's Rep. | PRK | 2019 | 6.051320e+04 |
| 1674 | Korea, Dem. People's Rep. | PRK | 2018 | 6.072550e+04 |
| 1675 | Korea, Dem. People's Rep. | PRK | 2017 | 6.093780e+04 |
| 1676 | Korea, Dem. People's Rep. | PRK | 2016 | 6.115010e+04 |
| 1677 | Korea, Dem. People's Rep. | PRK | 2015 | 6.136240e+04 |
| 1678 | Korea, Dem. People's Rep. | PRK | 2014 | 6.157470e+04 |
| 1679 | Korea, Dem. People's Rep. | PRK | 2013 | 6.178700e+04 |
| 1680 | Korea, Dem. People's Rep. | PRK | 2012 | 6.199930e+04 |
| 1681 | Korea, Dem. People's Rep. | PRK | 2011 | 6.221160e+04 |
| 1682 | Korea, Dem. People's Rep. | PRK | 2010 | 6.242390e+04 |
| 1683 | Korea, Rep. | KOR | 2020 | 6.287000e+04 |
| 1684 | Korea, Rep. | KOR | 2019 | 6.297000e+04 |
| 1685 | Korea, Rep. | KOR | 2018 | 6.307000e+04 |
| 1686 | Korea, Rep. | KOR | 2017 | 6.317000e+04 |
| 1687 | Korea, Rep. | KOR | 2016 | 6.325000e+04 |
| 1688 | Korea, Rep. | KOR | 2015 | 6.337000e+04 |
| 1689 | Korea, Rep. | KOR | 2014 | 6.347000e+04 |
| 1690 | Korea, Rep. | KOR | 2013 | 6.357000e+04 |
| 1691 | Korea, Rep. | KOR | 2012 | 6.367000e+04 |
| 1692 | Korea, Rep. | KOR | 2011 | 6.377000e+04 |
| 1693 | Korea, Rep. | KOR | 2010 | 6.387000e+04 |
| 1694 | Kosovo | XKX | 2020 | NaN |
| 1695 | Kosovo | XKX | 2019 | NaN |
| 1696 | Kosovo | XKX | 2018 | NaN |
| 1697 | Kosovo | XKX | 2017 | NaN |
| 1698 | Kosovo | XKX | 2016 | NaN |
| 1699 | Kosovo | XKX | 2015 | NaN |
| 1700 | Kosovo | XKX | 2014 | NaN |
| 1701 | Kosovo | XKX | 2013 | NaN |
| 1702 | Kosovo | XKX | 2012 | NaN |
| 1703 | Kosovo | XKX | 2011 | NaN |
| 1704 | Kosovo | XKX | 2010 | NaN |
| 1705 | Kuwait | KWT | 2020 | 6.250000e+01 |
| 1706 | Kuwait | KWT | 2019 | 6.250000e+01 |
| 1707 | Kuwait | KWT | 2018 | 6.250000e+01 |
| 1708 | Kuwait | KWT | 2017 | 6.250000e+01 |
| 1709 | Kuwait | KWT | 2016 | 6.250000e+01 |
| 1710 | Kuwait | KWT | 2015 | 6.250000e+01 |
| 1711 | Kuwait | KWT | 2014 | 6.250000e+01 |
| 1712 | Kuwait | KWT | 2013 | 6.250000e+01 |
| 1713 | Kuwait | KWT | 2012 | 6.250000e+01 |
| 1714 | Kuwait | KWT | 2011 | 6.250000e+01 |
| 1715 | Kuwait | KWT | 2010 | 6.250000e+01 |
| 1716 | Kyrgyz Republic | KGZ | 2020 | 1.315380e+04 |
| 1717 | Kyrgyz Republic | KGZ | 2019 | 1.297140e+04 |
| 1718 | Kyrgyz Republic | KGZ | 2018 | 1.278900e+04 |
| 1719 | Kyrgyz Republic | KGZ | 2017 | 1.260664e+04 |
| 1720 | Kyrgyz Republic | KGZ | 2016 | 1.256240e+04 |
| 1721 | Kyrgyz Republic | KGZ | 2015 | 1.251810e+04 |
| 1722 | Kyrgyz Republic | KGZ | 2014 | 1.247384e+04 |
| 1723 | Kyrgyz Republic | KGZ | 2013 | 1.242958e+04 |
| 1724 | Kyrgyz Republic | KGZ | 2012 | 1.238532e+04 |
| 1725 | Kyrgyz Republic | KGZ | 2011 | 1.234106e+04 |
| 1726 | Kyrgyz Republic | KGZ | 2010 | 1.229680e+04 |
| 1727 | Lao PDR | LAO | 2020 | 1.659550e+05 |
| 1728 | Lao PDR | LAO | 2019 | 1.663000e+05 |
| 1729 | Lao PDR | LAO | 2018 | 1.666450e+05 |
| 1730 | Lao PDR | LAO | 2017 | 1.669900e+05 |
| 1731 | Lao PDR | LAO | 2016 | 1.673350e+05 |
| 1732 | Lao PDR | LAO | 2015 | 1.676800e+05 |
| 1733 | Lao PDR | LAO | 2014 | 1.680250e+05 |
| 1734 | Lao PDR | LAO | 2013 | 1.683700e+05 |
| 1735 | Lao PDR | LAO | 2012 | 1.687150e+05 |
| 1736 | Lao PDR | LAO | 2011 | 1.690600e+05 |
| 1737 | Lao PDR | LAO | 2010 | 1.694050e+05 |
| 1738 | Latvia | LVA | 2020 | 3.410790e+04 |
| 1739 | Latvia | LVA | 2019 | 3.406920e+04 |
| 1740 | Latvia | LVA | 2018 | 3.403050e+04 |
| 1741 | Latvia | LVA | 2017 | 3.399180e+04 |
| 1742 | Latvia | LVA | 2016 | 3.395310e+04 |
| 1743 | Latvia | LVA | 2015 | 3.391440e+04 |
| 1744 | Latvia | LVA | 2014 | 3.387576e+04 |
| 1745 | Latvia | LVA | 2013 | 3.383712e+04 |
| 1746 | Latvia | LVA | 2012 | 3.379848e+04 |
| 1747 | Latvia | LVA | 2011 | 3.375984e+04 |
| 1748 | Latvia | LVA | 2010 | 3.372120e+04 |
| 1749 | Lebanon | LBN | 2020 | 1.433300e+03 |
| 1750 | Lebanon | LBN | 2019 | 1.427300e+03 |
| 1751 | Lebanon | LBN | 2018 | 1.421300e+03 |
| 1752 | Lebanon | LBN | 2017 | 1.415300e+03 |
| 1753 | Lebanon | LBN | 2016 | 1.409300e+03 |
| 1754 | Lebanon | LBN | 2015 | 1.403300e+03 |
| 1755 | Lebanon | LBN | 2014 | 1.397340e+03 |
| 1756 | Lebanon | LBN | 2013 | 1.391380e+03 |
| 1757 | Lebanon | LBN | 2012 | 1.385420e+03 |
| 1758 | Lebanon | LBN | 2011 | 1.379460e+03 |
| 1759 | Lebanon | LBN | 2010 | 1.373500e+03 |
| 1760 | Lesotho | LSO | 2020 | 3.452000e+02 |
| 1761 | Lesotho | LSO | 2019 | 3.452000e+02 |
| 1762 | Lesotho | LSO | 2018 | 3.452000e+02 |
| 1763 | Lesotho | LSO | 2017 | 3.452000e+02 |
| 1764 | Lesotho | LSO | 2016 | 3.452000e+02 |
| 1765 | Lesotho | LSO | 2015 | 3.452000e+02 |
| 1766 | Lesotho | LSO | 2014 | 3.452000e+02 |
| 1767 | Lesotho | LSO | 2013 | 3.452000e+02 |
| 1768 | Lesotho | LSO | 2012 | 3.452000e+02 |
| 1769 | Lesotho | LSO | 2011 | 3.452000e+02 |
| 1770 | Lesotho | LSO | 2010 | 3.452000e+02 |
| 1771 | Liberia | LBR | 2020 | 7.617440e+04 |
| 1772 | Liberia | LBR | 2019 | 7.647700e+04 |
| 1773 | Liberia | LBR | 2018 | 7.677960e+04 |
| 1774 | Liberia | LBR | 2017 | 7.708220e+04 |
| 1775 | Liberia | LBR | 2016 | 7.738480e+04 |
| 1776 | Liberia | LBR | 2015 | 7.768740e+04 |
| 1777 | Liberia | LBR | 2014 | 7.799000e+04 |
| 1778 | Liberia | LBR | 2013 | 7.829260e+04 |
| 1779 | Liberia | LBR | 2012 | 7.859520e+04 |
| 1780 | Liberia | LBR | 2011 | 7.889780e+04 |
| 1781 | Liberia | LBR | 2010 | 7.920040e+04 |
| 1782 | Libya | LBY | 2020 | 2.170000e+03 |
| 1783 | Libya | LBY | 2019 | 2.170000e+03 |
| 1784 | Libya | LBY | 2018 | 2.170000e+03 |
| 1785 | Libya | LBY | 2017 | 2.170000e+03 |
| 1786 | Libya | LBY | 2016 | 2.170000e+03 |
| 1787 | Libya | LBY | 2015 | 2.170000e+03 |
| 1788 | Libya | LBY | 2014 | 2.170000e+03 |
| 1789 | Libya | LBY | 2013 | 2.170000e+03 |
| 1790 | Libya | LBY | 2012 | 2.170000e+03 |
| 1791 | Libya | LBY | 2011 | 2.170000e+03 |
| 1792 | Libya | LBY | 2010 | 2.170000e+03 |
| 1793 | Liechtenstein | LIE | 2020 | 6.700000e+01 |
| 1794 | Liechtenstein | LIE | 2019 | 6.700000e+01 |
| 1795 | Liechtenstein | LIE | 2018 | 6.700000e+01 |
| 1796 | Liechtenstein | LIE | 2017 | 6.700000e+01 |
| 1797 | Liechtenstein | LIE | 2016 | 6.700000e+01 |
| 1798 | Liechtenstein | LIE | 2015 | 6.700000e+01 |
| 1799 | Liechtenstein | LIE | 2014 | 6.699800e+01 |
| 1800 | Liechtenstein | LIE | 2013 | 6.699700e+01 |
| 1801 | Liechtenstein | LIE | 2012 | 6.699500e+01 |
| 1802 | Liechtenstein | LIE | 2011 | 6.699400e+01 |
| 1803 | Liechtenstein | LIE | 2010 | 6.699200e+01 |
| 1804 | Lithuania | LTU | 2020 | 2.201000e+04 |
| 1805 | Lithuania | LTU | 2019 | 2.200000e+04 |
| 1806 | Lithuania | LTU | 2018 | 2.198000e+04 |
| 1807 | Lithuania | LTU | 2017 | 2.196000e+04 |
| 1808 | Lithuania | LTU | 2016 | 2.190000e+04 |
| 1809 | Lithuania | LTU | 2015 | 2.187000e+04 |
| 1810 | Lithuania | LTU | 2014 | 2.183600e+04 |
| 1811 | Lithuania | LTU | 2013 | 2.180200e+04 |
| 1812 | Lithuania | LTU | 2012 | 2.176800e+04 |
| 1813 | Lithuania | LTU | 2011 | 2.173400e+04 |
| 1814 | Lithuania | LTU | 2010 | 2.170000e+04 |
| 1815 | Luxembourg | LUX | 2020 | 8.870000e+02 |
| 1816 | Luxembourg | LUX | 2019 | 8.870000e+02 |
| 1817 | Luxembourg | LUX | 2018 | 8.870000e+02 |
| 1818 | Luxembourg | LUX | 2017 | 8.870000e+02 |
| 1819 | Luxembourg | LUX | 2016 | 8.870000e+02 |
| 1820 | Luxembourg | LUX | 2015 | 8.870000e+02 |
| 1821 | Luxembourg | LUX | 2014 | 8.870000e+02 |
| 1822 | Luxembourg | LUX | 2013 | 8.870000e+02 |
| 1823 | Luxembourg | LUX | 2012 | 8.870000e+02 |
| 1824 | Luxembourg | LUX | 2011 | 8.870000e+02 |
| 1825 | Luxembourg | LUX | 2010 | 8.870000e+02 |
| 1826 | Macao SAR, China | MAC | 2020 | NaN |
| 1827 | Macao SAR, China | MAC | 2019 | NaN |
| 1828 | Macao SAR, China | MAC | 2018 | NaN |
| 1829 | Macao SAR, China | MAC | 2017 | NaN |
| 1830 | Macao SAR, China | MAC | 2016 | NaN |
| 1831 | Macao SAR, China | MAC | 2015 | NaN |
| 1832 | Macao SAR, China | MAC | 2014 | NaN |
| 1833 | Macao SAR, China | MAC | 2013 | NaN |
| 1834 | Macao SAR, China | MAC | 2012 | NaN |
| 1835 | Macao SAR, China | MAC | 2011 | NaN |
| 1836 | Macao SAR, China | MAC | 2010 | NaN |
| 1837 | Madagascar | MDG | 2020 | 1.242981e+05 |
| 1838 | Madagascar | MDG | 2019 | 1.244303e+05 |
| 1839 | Madagascar | MDG | 2018 | 1.245624e+05 |
| 1840 | Madagascar | MDG | 2017 | 1.246946e+05 |
| 1841 | Madagascar | MDG | 2016 | 1.248268e+05 |
| 1842 | Madagascar | MDG | 2015 | 1.249589e+05 |
| 1843 | Madagascar | MDG | 2014 | 1.250911e+05 |
| 1844 | Madagascar | MDG | 2013 | 1.252233e+05 |
| 1845 | Madagascar | MDG | 2012 | 1.253554e+05 |
| 1846 | Madagascar | MDG | 2011 | 1.254876e+05 |
| 1847 | Madagascar | MDG | 2010 | 1.256198e+05 |
| 1848 | Malawi | MWI | 2020 | 2.241700e+04 |
| 1849 | Malawi | MWI | 2019 | 2.283700e+04 |
| 1850 | Malawi | MWI | 2018 | 2.325700e+04 |
| 1851 | Malawi | MWI | 2017 | 2.367700e+04 |
| 1852 | Malawi | MWI | 2016 | 2.409700e+04 |
| 1853 | Malawi | MWI | 2015 | 2.451700e+04 |
| 1854 | Malawi | MWI | 2014 | 2.493700e+04 |
| 1855 | Malawi | MWI | 2013 | 2.535700e+04 |
| 1856 | Malawi | MWI | 2012 | 2.577700e+04 |
| 1857 | Malawi | MWI | 2011 | 2.619700e+04 |
| 1858 | Malawi | MWI | 2010 | 2.661700e+04 |
| 1859 | Malaysia | MYS | 2020 | 1.911404e+05 |
| 1860 | Malaysia | MYS | 2019 | 1.916419e+05 |
| 1861 | Malaysia | MYS | 2018 | 1.921434e+05 |
| 1862 | Malaysia | MYS | 2017 | 1.926449e+05 |
| 1863 | Malaysia | MYS | 2016 | 1.931464e+05 |
| 1864 | Malaysia | MYS | 2015 | 1.946422e+05 |
| 1865 | Malaysia | MYS | 2014 | 1.936091e+05 |
| 1866 | Malaysia | MYS | 2013 | 1.925759e+05 |
| 1867 | Malaysia | MYS | 2012 | 1.915428e+05 |
| 1868 | Malaysia | MYS | 2011 | 1.905096e+05 |
| 1869 | Malaysia | MYS | 2010 | 1.894765e+05 |
| 1870 | Maldives | MDV | 2020 | 8.200000e+00 |
| 1871 | Maldives | MDV | 2019 | 8.200000e+00 |
| 1872 | Maldives | MDV | 2018 | 8.200000e+00 |
| 1873 | Maldives | MDV | 2017 | 8.200000e+00 |
| 1874 | Maldives | MDV | 2016 | 8.200000e+00 |
| 1875 | Maldives | MDV | 2015 | 8.200000e+00 |
| 1876 | Maldives | MDV | 2014 | 8.200000e+00 |
| 1877 | Maldives | MDV | 2013 | 8.200000e+00 |
| 1878 | Maldives | MDV | 2012 | 8.200000e+00 |
| 1879 | Maldives | MDV | 2011 | 8.200000e+00 |
| 1880 | Maldives | MDV | 2010 | 8.200000e+00 |
| 1881 | Mali | MLI | 2020 | 1.329600e+05 |
| 1882 | Mali | MLI | 2019 | 1.329600e+05 |
| 1883 | Mali | MLI | 2018 | 1.329600e+05 |
| 1884 | Mali | MLI | 2017 | 1.329600e+05 |
| 1885 | Mali | MLI | 2016 | 1.329600e+05 |
| 1886 | Mali | MLI | 2015 | 1.329600e+05 |
| 1887 | Mali | MLI | 2014 | 1.329600e+05 |
| 1888 | Mali | MLI | 2013 | 1.329600e+05 |
| 1889 | Mali | MLI | 2012 | 1.329600e+05 |
| 1890 | Mali | MLI | 2011 | 1.329600e+05 |
| 1891 | Mali | MLI | 2010 | 1.329600e+05 |
| 1892 | Malta | MLT | 2020 | 4.600000e+00 |
| 1893 | Malta | MLT | 2019 | 4.600000e+00 |
| 1894 | Malta | MLT | 2018 | 4.600000e+00 |
| 1895 | Malta | MLT | 2017 | 4.200000e+00 |
| 1896 | Malta | MLT | 2016 | 3.800000e+00 |
| 1897 | Malta | MLT | 2015 | 3.500000e+00 |
| 1898 | Malta | MLT | 2014 | 3.500000e+00 |
| 1899 | Malta | MLT | 2013 | 3.500000e+00 |
| 1900 | Malta | MLT | 2012 | 3.500000e+00 |
| 1901 | Malta | MLT | 2011 | 3.500000e+00 |
| 1902 | Malta | MLT | 2010 | 3.500000e+00 |
| 1903 | Marshall Islands | MHL | 2020 | 9.400000e+01 |
| 1904 | Marshall Islands | MHL | 2019 | 9.400000e+01 |
| 1905 | Marshall Islands | MHL | 2018 | 9.400000e+01 |
| 1906 | Marshall Islands | MHL | 2017 | 9.400000e+01 |
| 1907 | Marshall Islands | MHL | 2016 | 9.400000e+01 |
| 1908 | Marshall Islands | MHL | 2015 | 9.400000e+01 |
| 1909 | Marshall Islands | MHL | 2014 | 9.400000e+01 |
| 1910 | Marshall Islands | MHL | 2013 | 9.400000e+01 |
| 1911 | Marshall Islands | MHL | 2012 | 9.400000e+01 |
| 1912 | Marshall Islands | MHL | 2011 | 9.400000e+01 |
| 1913 | Marshall Islands | MHL | 2010 | 9.400000e+01 |
| 1914 | Mauritania | MRT | 2020 | 3.128000e+03 |
| 1915 | Mauritania | MRT | 2019 | 3.183000e+03 |
| 1916 | Mauritania | MRT | 2018 | 3.237000e+03 |
| 1917 | Mauritania | MRT | 2017 | 3.292000e+03 |
| 1918 | Mauritania | MRT | 2016 | 3.346000e+03 |
| 1919 | Mauritania | MRT | 2015 | 3.400400e+03 |
| 1920 | Mauritania | MRT | 2014 | 3.454800e+03 |
| 1921 | Mauritania | MRT | 2013 | 3.509200e+03 |
| 1922 | Mauritania | MRT | 2012 | 3.563600e+03 |
| 1923 | Mauritania | MRT | 2011 | 3.618000e+03 |
| 1924 | Mauritania | MRT | 2010 | 3.672400e+03 |
| 1925 | Mauritius | MUS | 2020 | 3.877000e+02 |
| 1926 | Mauritius | MUS | 2019 | 3.873000e+02 |
| 1927 | Mauritius | MUS | 2018 | 3.869000e+02 |
| 1928 | Mauritius | MUS | 2017 | 3.865000e+02 |
| 1929 | Mauritius | MUS | 2016 | 3.829000e+02 |
| 1930 | Mauritius | MUS | 2015 | 3.830000e+02 |
| 1931 | Mauritius | MUS | 2014 | 3.831800e+02 |
| 1932 | Mauritius | MUS | 2013 | 3.833600e+02 |
| 1933 | Mauritius | MUS | 2012 | 3.835400e+02 |
| 1934 | Mauritius | MUS | 2011 | 3.837200e+02 |
| 1935 | Mauritius | MUS | 2010 | 3.839000e+02 |
| 1936 | Mexico | MEX | 2020 | 6.569208e+05 |
| 1937 | Mexico | MEX | 2019 | 6.581985e+05 |
| 1938 | Mexico | MEX | 2018 | 6.594761e+05 |
| 1939 | Mexico | MEX | 2017 | 6.607538e+05 |
| 1940 | Mexico | MEX | 2016 | 6.620315e+05 |
| 1941 | Mexico | MEX | 2015 | 6.633091e+05 |
| 1942 | Mexico | MEX | 2014 | 6.645339e+05 |
| 1943 | Mexico | MEX | 2013 | 6.657587e+05 |
| 1944 | Mexico | MEX | 2012 | 6.669835e+05 |
| 1945 | Mexico | MEX | 2011 | 6.682083e+05 |
| 1946 | Mexico | MEX | 2010 | 6.694331e+05 |
| 1947 | Micronesia, Fed. Sts. | FSM | 2020 | 6.442000e+02 |
| 1948 | Micronesia, Fed. Sts. | FSM | 2019 | 6.439000e+02 |
| 1949 | Micronesia, Fed. Sts. | FSM | 2018 | 6.436000e+02 |
| 1950 | Micronesia, Fed. Sts. | FSM | 2017 | 6.433000e+02 |
| 1951 | Micronesia, Fed. Sts. | FSM | 2016 | 6.430000e+02 |
| 1952 | Micronesia, Fed. Sts. | FSM | 2015 | 6.427000e+02 |
| 1953 | Micronesia, Fed. Sts. | FSM | 2014 | 6.424200e+02 |
| 1954 | Micronesia, Fed. Sts. | FSM | 2013 | 6.421400e+02 |
| 1955 | Micronesia, Fed. Sts. | FSM | 2012 | 6.418600e+02 |
| 1956 | Micronesia, Fed. Sts. | FSM | 2011 | 6.415800e+02 |
| 1957 | Micronesia, Fed. Sts. | FSM | 2010 | 6.413000e+02 |
| 1958 | Moldova | MDA | 2020 | 3.865000e+03 |
| 1959 | Moldova | MDA | 2019 | 3.865000e+03 |
| 1960 | Moldova | MDA | 2018 | 3.865000e+03 |
| 1961 | Moldova | MDA | 2017 | 3.865000e+03 |
| 1962 | Moldova | MDA | 2016 | 3.865000e+03 |
| 1963 | Moldova | MDA | 2015 | 3.864000e+03 |
| 1964 | Moldova | MDA | 2014 | 3.840200e+03 |
| 1965 | Moldova | MDA | 2013 | 3.816400e+03 |
| 1966 | Moldova | MDA | 2012 | 3.792600e+03 |
| 1967 | Moldova | MDA | 2011 | 3.768800e+03 |
| 1968 | Moldova | MDA | 2010 | 3.745000e+03 |
| 1969 | Monaco | MCO | 2020 | 0.000000e+00 |
| 1970 | Monaco | MCO | 2019 | 0.000000e+00 |
| 1971 | Monaco | MCO | 2018 | 0.000000e+00 |
| 1972 | Monaco | MCO | 2017 | 0.000000e+00 |
| 1973 | Monaco | MCO | 2016 | 0.000000e+00 |
| 1974 | Monaco | MCO | 2015 | 0.000000e+00 |
| 1975 | Monaco | MCO | 2014 | 0.000000e+00 |
| 1976 | Monaco | MCO | 2013 | 0.000000e+00 |
| 1977 | Monaco | MCO | 2012 | 0.000000e+00 |
| 1978 | Monaco | MCO | 2011 | 0.000000e+00 |
| 1979 | Monaco | MCO | 2010 | 0.000000e+00 |
| 1980 | Mongolia | MNG | 2020 | 1.417278e+05 |
| 1981 | Mongolia | MNG | 2019 | 1.417389e+05 |
| 1982 | Mongolia | MNG | 2018 | 1.417500e+05 |
| 1983 | Mongolia | MNG | 2017 | 1.417611e+05 |
| 1984 | Mongolia | MNG | 2016 | 1.417722e+05 |
| 1985 | Mongolia | MNG | 2015 | 1.417833e+05 |
| 1986 | Mongolia | MNG | 2014 | 1.417944e+05 |
| 1987 | Mongolia | MNG | 2013 | 1.418056e+05 |
| 1988 | Mongolia | MNG | 2012 | 1.418167e+05 |
| 1989 | Mongolia | MNG | 2011 | 1.418279e+05 |
| 1990 | Mongolia | MNG | 2010 | 1.418390e+05 |
| 1991 | Montenegro | MNE | 2020 | 8.270000e+03 |
| 1992 | Montenegro | MNE | 2019 | 8.270000e+03 |
| 1993 | Montenegro | MNE | 2018 | 8.270000e+03 |
| 1994 | Montenegro | MNE | 2017 | 8.270000e+03 |
| 1995 | Montenegro | MNE | 2016 | 8.270000e+03 |
| 1996 | Montenegro | MNE | 2015 | 8.270000e+03 |
| 1997 | Montenegro | MNE | 2014 | 8.270000e+03 |
| 1998 | Montenegro | MNE | 2013 | 8.270000e+03 |
| 1999 | Montenegro | MNE | 2012 | 8.270000e+03 |
| 2000 | Montenegro | MNE | 2011 | 8.270000e+03 |
| 2001 | Montenegro | MNE | 2010 | 8.270000e+03 |
| 2002 | Morocco | MAR | 2020 | 5.742490e+04 |
| 2003 | Morocco | MAR | 2019 | 5.732090e+04 |
| 2004 | Morocco | MAR | 2018 | 5.721590e+04 |
| 2005 | Morocco | MAR | 2017 | 5.711590e+04 |
| 2006 | Morocco | MAR | 2016 | 5.699790e+04 |
| 2007 | Morocco | MAR | 2015 | 5.684690e+04 |
| 2008 | Morocco | MAR | 2014 | 5.682666e+04 |
| 2009 | Morocco | MAR | 2013 | 5.680642e+04 |
| 2010 | Morocco | MAR | 2012 | 5.678618e+04 |
| 2011 | Morocco | MAR | 2011 | 5.676594e+04 |
| 2012 | Morocco | MAR | 2010 | 5.674570e+04 |
| 2013 | Mozambique | MOZ | 2020 | 3.674376e+05 |
| 2014 | Mozambique | MOZ | 2019 | 3.696611e+05 |
| 2015 | Mozambique | MOZ | 2018 | 3.722417e+05 |
| 2016 | Mozambique | MOZ | 2017 | 3.740660e+05 |
| 2017 | Mozambique | MOZ | 2016 | 3.762829e+05 |
| 2018 | Mozambique | MOZ | 2015 | 3.794000e+05 |
| 2019 | Mozambique | MOZ | 2014 | 3.814643e+05 |
| 2020 | Mozambique | MOZ | 2013 | 3.835286e+05 |
| 2021 | Mozambique | MOZ | 2012 | 3.855928e+05 |
| 2022 | Mozambique | MOZ | 2011 | 3.876571e+05 |
| 2023 | Mozambique | MOZ | 2010 | 3.897214e+05 |
| 2024 | Myanmar | MMR | 2020 | 2.854389e+05 |
| 2025 | Myanmar | MMR | 2019 | 2.883360e+05 |
| 2026 | Myanmar | MMR | 2018 | 2.912331e+05 |
| 2027 | Myanmar | MMR | 2017 | 2.941302e+05 |
| 2028 | Myanmar | MMR | 2016 | 2.970273e+05 |
| 2029 | Myanmar | MMR | 2015 | 2.999244e+05 |
| 2030 | Myanmar | MMR | 2014 | 3.028215e+05 |
| 2031 | Myanmar | MMR | 2013 | 3.057186e+05 |
| 2032 | Myanmar | MMR | 2012 | 3.086158e+05 |
| 2033 | Myanmar | MMR | 2011 | 3.115129e+05 |
| 2034 | Myanmar | MMR | 2010 | 3.144100e+05 |
| 2035 | Namibia | NAM | 2020 | 6.638900e+04 |
| 2036 | Namibia | NAM | 2019 | 6.709910e+04 |
| 2037 | Namibia | NAM | 2018 | 6.780920e+04 |
| 2038 | Namibia | NAM | 2017 | 6.851930e+04 |
| 2039 | Namibia | NAM | 2016 | 6.922940e+04 |
| 2040 | Namibia | NAM | 2015 | 6.993950e+04 |
| 2041 | Namibia | NAM | 2014 | 7.064958e+04 |
| 2042 | Namibia | NAM | 2013 | 7.135966e+04 |
| 2043 | Namibia | NAM | 2012 | 7.206974e+04 |
| 2044 | Namibia | NAM | 2011 | 7.277982e+04 |
| 2045 | Namibia | NAM | 2010 | 7.348990e+04 |
| 2046 | Nauru | NRU | 2020 | 0.000000e+00 |
| 2047 | Nauru | NRU | 2019 | 0.000000e+00 |
| 2048 | Nauru | NRU | 2018 | 0.000000e+00 |
| 2049 | Nauru | NRU | 2017 | 0.000000e+00 |
| 2050 | Nauru | NRU | 2016 | 0.000000e+00 |
| 2051 | Nauru | NRU | 2015 | 0.000000e+00 |
| 2052 | Nauru | NRU | 2014 | 0.000000e+00 |
| 2053 | Nauru | NRU | 2013 | 0.000000e+00 |
| 2054 | Nauru | NRU | 2012 | 0.000000e+00 |
| 2055 | Nauru | NRU | 2011 | 0.000000e+00 |
| 2056 | Nauru | NRU | 2010 | 0.000000e+00 |
| 2057 | Nepal | NPL | 2020 | 5.962030e+04 |
| 2058 | Nepal | NPL | 2019 | 5.962030e+04 |
| 2059 | Nepal | NPL | 2018 | 5.962030e+04 |
| 2060 | Nepal | NPL | 2017 | 5.962030e+04 |
| 2061 | Nepal | NPL | 2016 | 5.962030e+04 |
| 2062 | Nepal | NPL | 2015 | 5.962030e+04 |
| 2063 | Nepal | NPL | 2014 | 5.962030e+04 |
| 2064 | Nepal | NPL | 2013 | 5.962030e+04 |
| 2065 | Nepal | NPL | 2012 | 5.962030e+04 |
| 2066 | Nepal | NPL | 2011 | 5.962030e+04 |
| 2067 | Nepal | NPL | 2010 | 5.962030e+04 |
| 2068 | Netherlands | NLD | 2020 | 3.695000e+03 |
| 2069 | Netherlands | NLD | 2019 | 3.685700e+03 |
| 2070 | Netherlands | NLD | 2018 | 3.676300e+03 |
| 2071 | Netherlands | NLD | 2017 | 3.667000e+03 |
| 2072 | Netherlands | NLD | 2016 | 3.657600e+03 |
| 2073 | Netherlands | NLD | 2015 | 3.648300e+03 |
| 2074 | Netherlands | NLD | 2014 | 3.665600e+03 |
| 2075 | Netherlands | NLD | 2013 | 3.682900e+03 |
| 2076 | Netherlands | NLD | 2012 | 3.700200e+03 |
| 2077 | Netherlands | NLD | 2011 | 3.717500e+03 |
| 2078 | Netherlands | NLD | 2010 | 3.734800e+03 |
| 2079 | New Caledonia | NCL | 2020 | 8.380200e+03 |
| 2080 | New Caledonia | NCL | 2019 | 8.381200e+03 |
| 2081 | New Caledonia | NCL | 2018 | 8.382200e+03 |
| 2082 | New Caledonia | NCL | 2017 | 8.383200e+03 |
| 2083 | New Caledonia | NCL | 2016 | 8.384200e+03 |
| 2084 | New Caledonia | NCL | 2015 | 8.385200e+03 |
| 2085 | New Caledonia | NCL | 2014 | 8.386200e+03 |
| 2086 | New Caledonia | NCL | 2013 | 8.387200e+03 |
| 2087 | New Caledonia | NCL | 2012 | 8.388200e+03 |
| 2088 | New Caledonia | NCL | 2011 | 8.389200e+03 |
| 2089 | New Caledonia | NCL | 2010 | 8.390200e+03 |
| 2090 | New Zealand | NZL | 2020 | 9.892590e+04 |
| 2091 | New Zealand | NZL | 2019 | 9.865520e+04 |
| 2092 | New Zealand | NZL | 2018 | 9.855150e+04 |
| 2093 | New Zealand | NZL | 2017 | 9.850850e+04 |
| 2094 | New Zealand | NZL | 2016 | 9.846750e+04 |
| 2095 | New Zealand | NZL | 2015 | 9.846610e+04 |
| 2096 | New Zealand | NZL | 2014 | 9.846912e+04 |
| 2097 | New Zealand | NZL | 2013 | 9.847214e+04 |
| 2098 | New Zealand | NZL | 2012 | 9.847516e+04 |
| 2099 | New Zealand | NZL | 2011 | 9.847818e+04 |
| 2100 | New Zealand | NZL | 2010 | 9.848120e+04 |
| 2101 | Nicaragua | NIC | 2020 | 3.407530e+04 |
| 2102 | Nicaragua | NIC | 2019 | 3.507530e+04 |
| 2103 | Nicaragua | NIC | 2018 | 3.607530e+04 |
| 2104 | Nicaragua | NIC | 2017 | 3.707530e+04 |
| 2105 | Nicaragua | NIC | 2016 | 3.807530e+04 |
| 2106 | Nicaragua | NIC | 2015 | 3.907530e+04 |
| 2107 | Nicaragua | NIC | 2014 | 3.963654e+04 |
| 2108 | Nicaragua | NIC | 2013 | 4.019778e+04 |
| 2109 | Nicaragua | NIC | 2012 | 4.075902e+04 |
| 2110 | Nicaragua | NIC | 2011 | 4.132026e+04 |
| 2111 | Nicaragua | NIC | 2010 | 4.188150e+04 |
| 2112 | Niger | NER | 2020 | 1.079700e+04 |
| 2113 | Niger | NER | 2019 | 1.092120e+04 |
| 2114 | Niger | NER | 2018 | 1.104540e+04 |
| 2115 | Niger | NER | 2017 | 1.116960e+04 |
| 2116 | Niger | NER | 2016 | 1.129380e+04 |
| 2117 | Niger | NER | 2015 | 1.141800e+04 |
| 2118 | Niger | NER | 2014 | 1.154220e+04 |
| 2119 | Niger | NER | 2013 | 1.166640e+04 |
| 2120 | Niger | NER | 2012 | 1.179060e+04 |
| 2121 | Niger | NER | 2011 | 1.191480e+04 |
| 2122 | Niger | NER | 2010 | 1.203900e+04 |
| 2123 | Nigeria | NGA | 2020 | 2.162695e+05 |
| 2124 | Nigeria | NGA | 2019 | 2.179025e+05 |
| 2125 | Nigeria | NGA | 2018 | 2.195355e+05 |
| 2126 | Nigeria | NGA | 2017 | 2.211685e+05 |
| 2127 | Nigeria | NGA | 2016 | 2.228015e+05 |
| 2128 | Nigeria | NGA | 2015 | 2.244345e+05 |
| 2129 | Nigeria | NGA | 2014 | 2.260676e+05 |
| 2130 | Nigeria | NGA | 2013 | 2.277006e+05 |
| 2131 | Nigeria | NGA | 2012 | 2.293337e+05 |
| 2132 | Nigeria | NGA | 2011 | 2.309667e+05 |
| 2133 | Nigeria | NGA | 2010 | 2.325998e+05 |
| 2134 | North Macedonia | MKD | 2020 | 1.001490e+04 |
| 2135 | North Macedonia | MKD | 2019 | 1.001490e+04 |
| 2136 | North Macedonia | MKD | 2018 | 1.001490e+04 |
| 2137 | North Macedonia | MKD | 2017 | 1.001490e+04 |
| 2138 | North Macedonia | MKD | 2016 | 1.001670e+04 |
| 2139 | North Macedonia | MKD | 2015 | 9.944000e+03 |
| 2140 | North Macedonia | MKD | 2014 | 9.876060e+03 |
| 2141 | North Macedonia | MKD | 2013 | 9.808120e+03 |
| 2142 | North Macedonia | MKD | 2012 | 9.740180e+03 |
| 2143 | North Macedonia | MKD | 2011 | 9.672240e+03 |
| 2144 | North Macedonia | MKD | 2010 | 9.604300e+03 |
| 2145 | Northern Mariana Islands | MNP | 2020 | 2.436000e+02 |
| 2146 | Northern Mariana Islands | MNP | 2019 | 2.436000e+02 |
| 2147 | Northern Mariana Islands | MNP | 2018 | 2.436000e+02 |
| 2148 | Northern Mariana Islands | MNP | 2017 | 2.436000e+02 |
| 2149 | Northern Mariana Islands | MNP | 2016 | 2.436000e+02 |
| 2150 | Northern Mariana Islands | MNP | 2015 | 2.949000e+02 |
| 2151 | Northern Mariana Islands | MNP | 2014 | 2.965600e+02 |
| 2152 | Northern Mariana Islands | MNP | 2013 | 2.982200e+02 |
| 2153 | Northern Mariana Islands | MNP | 2012 | 2.998800e+02 |
| 2154 | Northern Mariana Islands | MNP | 2011 | 3.015400e+02 |
| 2155 | Northern Mariana Islands | MNP | 2010 | 3.032000e+02 |
| 2156 | Norway | NOR | 2020 | 1.218000e+05 |
| 2157 | Norway | NOR | 2019 | 1.217220e+05 |
| 2158 | Norway | NOR | 2018 | 1.216440e+05 |
| 2159 | Norway | NOR | 2017 | 1.215660e+05 |
| 2160 | Norway | NOR | 2016 | 1.214880e+05 |
| 2161 | Norway | NOR | 2015 | 1.214100e+05 |
| 2162 | Norway | NOR | 2014 | 1.213320e+05 |
| 2163 | Norway | NOR | 2013 | 1.212540e+05 |
| 2164 | Norway | NOR | 2012 | 1.211760e+05 |
| 2165 | Norway | NOR | 2011 | 1.210980e+05 |
| 2166 | Norway | NOR | 2010 | 1.210200e+05 |
| 2167 | Oman | OMN | 2020 | 2.500000e+01 |
| 2168 | Oman | OMN | 2019 | 2.500000e+01 |
| 2169 | Oman | OMN | 2018 | 2.600000e+01 |
| 2170 | Oman | OMN | 2017 | 2.700000e+01 |
| 2171 | Oman | OMN | 2016 | 2.800000e+01 |
| 2172 | Oman | OMN | 2015 | 3.000000e+01 |
| 2173 | Oman | OMN | 2014 | 3.000000e+01 |
| 2174 | Oman | OMN | 2013 | 3.000000e+01 |
| 2175 | Oman | OMN | 2012 | 3.000000e+01 |
| 2176 | Oman | OMN | 2011 | 3.000000e+01 |
| 2177 | Oman | OMN | 2010 | 3.000000e+01 |
| 2178 | Pakistan | PAK | 2020 | 3.725900e+04 |
| 2179 | Pakistan | PAK | 2019 | 3.767240e+04 |
| 2180 | Pakistan | PAK | 2018 | 3.808580e+04 |
| 2181 | Pakistan | PAK | 2017 | 3.849920e+04 |
| 2182 | Pakistan | PAK | 2016 | 3.868240e+04 |
| 2183 | Pakistan | PAK | 2015 | 3.932600e+04 |
| 2184 | Pakistan | PAK | 2014 | 3.964826e+04 |
| 2185 | Pakistan | PAK | 2013 | 3.997052e+04 |
| 2186 | Pakistan | PAK | 2012 | 4.029278e+04 |
| 2187 | Pakistan | PAK | 2011 | 4.061504e+04 |
| 2188 | Pakistan | PAK | 2010 | 4.093730e+04 |
| 2189 | Palau | PLW | 2020 | 4.141000e+02 |
| 2190 | Palau | PLW | 2019 | 4.133000e+02 |
| 2191 | Palau | PLW | 2018 | 4.125000e+02 |
| 2192 | Palau | PLW | 2017 | 4.116000e+02 |
| 2193 | Palau | PLW | 2016 | 4.108000e+02 |
| 2194 | Palau | PLW | 2015 | 4.099000e+02 |
| 2195 | Palau | PLW | 2014 | 4.090400e+02 |
| 2196 | Palau | PLW | 2013 | 4.081800e+02 |
| 2197 | Palau | PLW | 2012 | 4.073200e+02 |
| 2198 | Palau | PLW | 2011 | 4.064600e+02 |
| 2199 | Palau | PLW | 2010 | 4.056000e+02 |
| 2200 | Panama | PAN | 2020 | 4.213840e+04 |
| 2201 | Panama | PAN | 2019 | 4.225250e+04 |
| 2202 | Panama | PAN | 2018 | 4.236670e+04 |
| 2203 | Panama | PAN | 2017 | 4.248080e+04 |
| 2204 | Panama | PAN | 2016 | 4.259500e+04 |
| 2205 | Panama | PAN | 2015 | 4.270910e+04 |
| 2206 | Panama | PAN | 2014 | 4.282326e+04 |
| 2207 | Panama | PAN | 2013 | 4.293742e+04 |
| 2208 | Panama | PAN | 2012 | 4.305158e+04 |
| 2209 | Panama | PAN | 2011 | 4.316574e+04 |
| 2210 | Panama | PAN | 2010 | 4.327990e+04 |
| 2211 | Papua New Guinea | PNG | 2020 | 3.585576e+05 |
| 2212 | Papua New Guinea | PNG | 2019 | 3.588929e+05 |
| 2213 | Papua New Guinea | PNG | 2018 | 3.592282e+05 |
| 2214 | Papua New Guinea | PNG | 2017 | 3.595635e+05 |
| 2215 | Papua New Guinea | PNG | 2016 | 3.598988e+05 |
| 2216 | Papua New Guinea | PNG | 2015 | 3.602442e+05 |
| 2217 | Papua New Guinea | PNG | 2014 | 3.605531e+05 |
| 2218 | Papua New Guinea | PNG | 2013 | 3.608621e+05 |
| 2219 | Papua New Guinea | PNG | 2012 | 3.611710e+05 |
| 2220 | Papua New Guinea | PNG | 2011 | 3.614799e+05 |
| 2221 | Papua New Guinea | PNG | 2010 | 3.617889e+05 |
| 2222 | Paraguay | PRY | 2020 | 1.610226e+05 |
| 2223 | Paraguay | PRY | 2019 | 1.638160e+05 |
| 2224 | Paraguay | PRY | 2018 | 1.666093e+05 |
| 2225 | Paraguay | PRY | 2017 | 1.694027e+05 |
| 2226 | Paraguay | PRY | 2016 | 1.733313e+05 |
| 2227 | Paraguay | PRY | 2015 | 1.749894e+05 |
| 2228 | Paraguay | PRY | 2014 | 1.791319e+05 |
| 2229 | Paraguay | PRY | 2013 | 1.832745e+05 |
| 2230 | Paraguay | PRY | 2012 | 1.874170e+05 |
| 2231 | Paraguay | PRY | 2011 | 1.915596e+05 |
| 2232 | Paraguay | PRY | 2010 | 1.957021e+05 |
| 2233 | Peru | PER | 2020 | 7.233037e+05 |
| 2234 | Peru | PER | 2019 | 7.250320e+05 |
| 2235 | Peru | PER | 2018 | 7.267604e+05 |
| 2236 | Peru | PER | 2017 | 7.283478e+05 |
| 2237 | Peru | PER | 2016 | 7.301028e+05 |
| 2238 | Peru | PER | 2015 | 7.319453e+05 |
| 2239 | Peru | PER | 2014 | 7.336558e+05 |
| 2240 | Peru | PER | 2013 | 7.353664e+05 |
| 2241 | Peru | PER | 2012 | 7.370769e+05 |
| 2242 | Peru | PER | 2011 | 7.387875e+05 |
| 2243 | Peru | PER | 2010 | 7.404980e+05 |
| 2244 | Philippines | PHL | 2020 | 7.188590e+04 |
| 2245 | Philippines | PHL | 2019 | 7.153700e+04 |
| 2246 | Philippines | PHL | 2018 | 7.118810e+04 |
| 2247 | Philippines | PHL | 2017 | 7.083930e+04 |
| 2248 | Philippines | PHL | 2016 | 7.049040e+04 |
| 2249 | Philippines | PHL | 2015 | 7.014150e+04 |
| 2250 | Philippines | PHL | 2014 | 6.979264e+04 |
| 2251 | Philippines | PHL | 2013 | 6.944378e+04 |
| 2252 | Philippines | PHL | 2012 | 6.909492e+04 |
| 2253 | Philippines | PHL | 2011 | 6.874606e+04 |
| 2254 | Philippines | PHL | 2010 | 6.839720e+04 |
| 2255 | Poland | POL | 2020 | 9.483000e+04 |
| 2256 | Poland | POL | 2019 | 9.471000e+04 |
| 2257 | Poland | POL | 2018 | 9.459000e+04 |
| 2258 | Poland | POL | 2017 | 9.447000e+04 |
| 2259 | Poland | POL | 2016 | 9.435000e+04 |
| 2260 | Poland | POL | 2015 | 9.420000e+04 |
| 2261 | Poland | POL | 2014 | 9.401800e+04 |
| 2262 | Poland | POL | 2013 | 9.383600e+04 |
| 2263 | Poland | POL | 2012 | 9.365400e+04 |
| 2264 | Poland | POL | 2011 | 9.347200e+04 |
| 2265 | Poland | POL | 2010 | 9.329000e+04 |
| 2266 | Portugal | PRT | 2020 | 3.312000e+04 |
| 2267 | Portugal | PRT | 2019 | 3.312000e+04 |
| 2268 | Portugal | PRT | 2018 | 3.312000e+04 |
| 2269 | Portugal | PRT | 2017 | 3.312000e+04 |
| 2270 | Portugal | PRT | 2016 | 3.312000e+04 |
| 2271 | Portugal | PRT | 2015 | 3.312000e+04 |
| 2272 | Portugal | PRT | 2014 | 3.300000e+04 |
| 2273 | Portugal | PRT | 2013 | 3.288000e+04 |
| 2274 | Portugal | PRT | 2012 | 3.276000e+04 |
| 2275 | Portugal | PRT | 2011 | 3.264000e+04 |
| 2276 | Portugal | PRT | 2010 | 3.252000e+04 |
| 2277 | Puerto Rico | PRI | 2020 | 4.963300e+03 |
| 2278 | Puerto Rico | PRI | 2019 | 4.958400e+03 |
| 2279 | Puerto Rico | PRI | 2018 | 4.953500e+03 |
| 2280 | Puerto Rico | PRI | 2017 | 4.948600e+03 |
| 2281 | Puerto Rico | PRI | 2016 | 4.943700e+03 |
| 2282 | Puerto Rico | PRI | 2015 | 4.938800e+03 |
| 2283 | Puerto Rico | PRI | 2014 | 4.933940e+03 |
| 2284 | Puerto Rico | PRI | 2013 | 4.929080e+03 |
| 2285 | Puerto Rico | PRI | 2012 | 4.924220e+03 |
| 2286 | Puerto Rico | PRI | 2011 | 4.919360e+03 |
| 2287 | Puerto Rico | PRI | 2010 | 4.914500e+03 |
| 2288 | Qatar | QAT | 2020 | 0.000000e+00 |
| 2289 | Qatar | QAT | 2019 | 0.000000e+00 |
| 2290 | Qatar | QAT | 2018 | 0.000000e+00 |
| 2291 | Qatar | QAT | 2017 | 0.000000e+00 |
| 2292 | Qatar | QAT | 2016 | 0.000000e+00 |
| 2293 | Qatar | QAT | 2015 | 0.000000e+00 |
| 2294 | Qatar | QAT | 2014 | 0.000000e+00 |
| 2295 | Qatar | QAT | 2013 | 0.000000e+00 |
| 2296 | Qatar | QAT | 2012 | 0.000000e+00 |
| 2297 | Qatar | QAT | 2011 | 0.000000e+00 |
| 2298 | Qatar | QAT | 2010 | 0.000000e+00 |
| 2299 | Romania | ROU | 2020 | 6.929050e+04 |
| 2300 | Romania | ROU | 2019 | 6.929050e+04 |
| 2301 | Romania | ROU | 2018 | 6.929050e+04 |
| 2302 | Romania | ROU | 2017 | 6.929050e+04 |
| 2303 | Romania | ROU | 2016 | 6.929050e+04 |
| 2304 | Romania | ROU | 2015 | 6.900960e+04 |
| 2305 | Romania | ROU | 2014 | 6.823768e+04 |
| 2306 | Romania | ROU | 2013 | 6.746576e+04 |
| 2307 | Romania | ROU | 2012 | 6.669384e+04 |
| 2308 | Romania | ROU | 2011 | 6.592192e+04 |
| 2309 | Romania | ROU | 2010 | 6.515000e+04 |
| 2310 | Russian Federation | RUS | 2020 | 8.153116e+06 |
| 2311 | Russian Federation | RUS | 2019 | 8.153116e+06 |
| 2312 | Russian Federation | RUS | 2018 | 8.153116e+06 |
| 2313 | Russian Federation | RUS | 2017 | 8.153116e+06 |
| 2314 | Russian Federation | RUS | 2016 | 8.151210e+06 |
| 2315 | Russian Federation | RUS | 2015 | 8.149305e+06 |
| 2316 | Russian Federation | RUS | 2014 | 8.149715e+06 |
| 2317 | Russian Federation | RUS | 2013 | 8.150125e+06 |
| 2318 | Russian Federation | RUS | 2012 | 8.150535e+06 |
| 2319 | Russian Federation | RUS | 2011 | 8.150946e+06 |
| 2320 | Russian Federation | RUS | 2010 | 8.151356e+06 |
| 2321 | Rwanda | RWA | 2020 | 2.760000e+03 |
| 2322 | Rwanda | RWA | 2019 | 2.750000e+03 |
| 2323 | Rwanda | RWA | 2018 | 2.740000e+03 |
| 2324 | Rwanda | RWA | 2017 | 2.730000e+03 |
| 2325 | Rwanda | RWA | 2016 | 2.720000e+03 |
| 2326 | Rwanda | RWA | 2015 | 2.700000e+03 |
| 2327 | Rwanda | RWA | 2014 | 2.690000e+03 |
| 2328 | Rwanda | RWA | 2013 | 2.680000e+03 |
| 2329 | Rwanda | RWA | 2012 | 2.670000e+03 |
| 2330 | Rwanda | RWA | 2011 | 2.660000e+03 |
| 2331 | Rwanda | RWA | 2010 | 2.650000e+03 |
| 2332 | Samoa | WSM | 2020 | 1.616700e+03 |
| 2333 | Samoa | WSM | 2019 | 1.621500e+03 |
| 2334 | Samoa | WSM | 2018 | 1.626300e+03 |
| 2335 | Samoa | WSM | 2017 | 1.631100e+03 |
| 2336 | Samoa | WSM | 2016 | 1.635900e+03 |
| 2337 | Samoa | WSM | 2015 | 1.640700e+03 |
| 2338 | Samoa | WSM | 2014 | 1.645540e+03 |
| 2339 | Samoa | WSM | 2013 | 1.650380e+03 |
| 2340 | Samoa | WSM | 2012 | 1.655220e+03 |
| 2341 | Samoa | WSM | 2011 | 1.660060e+03 |
| 2342 | Samoa | WSM | 2010 | 1.664900e+03 |
| 2343 | San Marino | SMR | 2020 | 1.000000e+01 |
| 2344 | San Marino | SMR | 2019 | 1.000000e+01 |
| 2345 | San Marino | SMR | 2018 | 1.000000e+01 |
| 2346 | San Marino | SMR | 2017 | 1.000000e+01 |
| 2347 | San Marino | SMR | 2016 | 1.000000e+01 |
| 2348 | San Marino | SMR | 2015 | 1.000000e+01 |
| 2349 | San Marino | SMR | 2014 | 1.000000e+01 |
| 2350 | San Marino | SMR | 2013 | 1.000000e+01 |
| 2351 | San Marino | SMR | 2012 | 1.000000e+01 |
| 2352 | San Marino | SMR | 2011 | 1.000000e+01 |
| 2353 | San Marino | SMR | 2010 | 1.000000e+01 |
| 2354 | Sao Tome and Principe | STP | 2020 | 5.190000e+02 |
| 2355 | Sao Tome and Principe | STP | 2019 | 5.252000e+02 |
| 2356 | Sao Tome and Principe | STP | 2018 | 5.314000e+02 |
| 2357 | Sao Tome and Principe | STP | 2017 | 5.376000e+02 |
| 2358 | Sao Tome and Principe | STP | 2016 | 5.438000e+02 |
| 2359 | Sao Tome and Principe | STP | 2015 | 5.500000e+02 |
| 2360 | Sao Tome and Principe | STP | 2014 | 5.562000e+02 |
| 2361 | Sao Tome and Principe | STP | 2013 | 5.624000e+02 |
| 2362 | Sao Tome and Principe | STP | 2012 | 5.686000e+02 |
| 2363 | Sao Tome and Principe | STP | 2011 | 5.748000e+02 |
| 2364 | Sao Tome and Principe | STP | 2010 | 5.810000e+02 |
| 2365 | Saudi Arabia | SAU | 2020 | 9.770000e+03 |
| 2366 | Saudi Arabia | SAU | 2019 | 9.770000e+03 |
| 2367 | Saudi Arabia | SAU | 2018 | 9.770000e+03 |
| 2368 | Saudi Arabia | SAU | 2017 | 9.770000e+03 |
| 2369 | Saudi Arabia | SAU | 2016 | 9.770000e+03 |
| 2370 | Saudi Arabia | SAU | 2015 | 9.770000e+03 |
| 2371 | Saudi Arabia | SAU | 2014 | 9.770000e+03 |
| 2372 | Saudi Arabia | SAU | 2013 | 9.770000e+03 |
| 2373 | Saudi Arabia | SAU | 2012 | 9.770000e+03 |
| 2374 | Saudi Arabia | SAU | 2011 | 9.770000e+03 |
| 2375 | Saudi Arabia | SAU | 2010 | 9.770000e+03 |
| 2376 | Senegal | SEN | 2020 | 8.068160e+04 |
| 2377 | Senegal | SEN | 2019 | 8.108160e+04 |
| 2378 | Senegal | SEN | 2018 | 8.148160e+04 |
| 2379 | Senegal | SEN | 2017 | 8.188160e+04 |
| 2380 | Senegal | SEN | 2016 | 8.228160e+04 |
| 2381 | Senegal | SEN | 2015 | 8.268160e+04 |
| 2382 | Senegal | SEN | 2014 | 8.308160e+04 |
| 2383 | Senegal | SEN | 2013 | 8.348160e+04 |
| 2384 | Senegal | SEN | 2012 | 8.388160e+04 |
| 2385 | Senegal | SEN | 2011 | 8.428160e+04 |
| 2386 | Senegal | SEN | 2010 | 8.468160e+04 |
| 2387 | Serbia | SRB | 2020 | 2.722650e+04 |
| 2388 | Serbia | SRB | 2019 | 2.722220e+04 |
| 2389 | Serbia | SRB | 2018 | 2.722000e+04 |
| 2390 | Serbia | SRB | 2017 | 2.721860e+04 |
| 2391 | Serbia | SRB | 2016 | 2.720180e+04 |
| 2392 | Serbia | SRB | 2015 | 2.719530e+04 |
| 2393 | Serbia | SRB | 2014 | 2.718224e+04 |
| 2394 | Serbia | SRB | 2013 | 2.716918e+04 |
| 2395 | Serbia | SRB | 2012 | 2.715612e+04 |
| 2396 | Serbia | SRB | 2011 | 2.714306e+04 |
| 2397 | Serbia | SRB | 2010 | 2.713000e+04 |
| 2398 | Seychelles | SYC | 2020 | 3.370000e+02 |
| 2399 | Seychelles | SYC | 2019 | 3.370000e+02 |
| 2400 | Seychelles | SYC | 2018 | 3.370000e+02 |
| 2401 | Seychelles | SYC | 2017 | 3.370000e+02 |
| 2402 | Seychelles | SYC | 2016 | 3.370000e+02 |
| 2403 | Seychelles | SYC | 2015 | 3.370000e+02 |
| 2404 | Seychelles | SYC | 2014 | 3.370000e+02 |
| 2405 | Seychelles | SYC | 2013 | 3.370000e+02 |
| 2406 | Seychelles | SYC | 2012 | 3.370000e+02 |
| 2407 | Seychelles | SYC | 2011 | 3.370000e+02 |
| 2408 | Seychelles | SYC | 2010 | 3.370000e+02 |
| 2409 | Sierra Leone | SLE | 2020 | 2.534880e+04 |
| 2410 | Sierra Leone | SLE | 2019 | 2.554610e+04 |
| 2411 | Sierra Leone | SLE | 2018 | 2.574340e+04 |
| 2412 | Sierra Leone | SLE | 2017 | 2.594070e+04 |
| 2413 | Sierra Leone | SLE | 2016 | 2.613800e+04 |
| 2414 | Sierra Leone | SLE | 2015 | 2.633530e+04 |
| 2415 | Sierra Leone | SLE | 2014 | 2.653256e+04 |
| 2416 | Sierra Leone | SLE | 2013 | 2.672982e+04 |
| 2417 | Sierra Leone | SLE | 2012 | 2.692708e+04 |
| 2418 | Sierra Leone | SLE | 2011 | 2.712434e+04 |
| 2419 | Sierra Leone | SLE | 2010 | 2.732160e+04 |
| 2420 | Singapore | SGP | 2020 | 1.557000e+02 |
| 2421 | Singapore | SGP | 2019 | 1.575000e+02 |
| 2422 | Singapore | SGP | 2018 | 1.593000e+02 |
| 2423 | Singapore | SGP | 2017 | 1.611000e+02 |
| 2424 | Singapore | SGP | 2016 | 1.628550e+02 |
| 2425 | Singapore | SGP | 2015 | 1.647140e+02 |
| 2426 | Singapore | SGP | 2014 | 1.672520e+02 |
| 2427 | Singapore | SGP | 2013 | 1.697900e+02 |
| 2428 | Singapore | SGP | 2012 | 1.723280e+02 |
| 2429 | Singapore | SGP | 2011 | 1.748660e+02 |
| 2430 | Singapore | SGP | 2010 | 1.774040e+02 |
| 2431 | Sint Maarten (Dutch part) | SXM | 2020 | 3.700000e+00 |
| 2432 | Sint Maarten (Dutch part) | SXM | 2019 | 3.700000e+00 |
| 2433 | Sint Maarten (Dutch part) | SXM | 2018 | 3.700000e+00 |
| 2434 | Sint Maarten (Dutch part) | SXM | 2017 | 3.700000e+00 |
| 2435 | Sint Maarten (Dutch part) | SXM | 2016 | 3.700000e+00 |
| 2436 | Sint Maarten (Dutch part) | SXM | 2015 | 3.700000e+00 |
| 2437 | Sint Maarten (Dutch part) | SXM | 2014 | 3.700000e+00 |
| 2438 | Sint Maarten (Dutch part) | SXM | 2013 | 3.700000e+00 |
| 2439 | Sint Maarten (Dutch part) | SXM | 2012 | 3.700000e+00 |
| 2440 | Sint Maarten (Dutch part) | SXM | 2011 | 3.700000e+00 |
| 2441 | Sint Maarten (Dutch part) | SXM | 2010 | NaN |
| 2442 | Slovak Republic | SVK | 2020 | 1.925900e+04 |
| 2443 | Slovak Republic | SVK | 2019 | 1.925900e+04 |
| 2444 | Slovak Republic | SVK | 2018 | 1.925900e+04 |
| 2445 | Slovak Republic | SVK | 2017 | 1.925900e+04 |
| 2446 | Slovak Republic | SVK | 2016 | 1.923370e+04 |
| 2447 | Slovak Republic | SVK | 2015 | 1.921750e+04 |
| 2448 | Slovak Republic | SVK | 2014 | 1.920982e+04 |
| 2449 | Slovak Republic | SVK | 2013 | 1.920214e+04 |
| 2450 | Slovak Republic | SVK | 2012 | 1.919446e+04 |
| 2451 | Slovak Republic | SVK | 2011 | 1.918678e+04 |
| 2452 | Slovak Republic | SVK | 2010 | 1.917910e+04 |
| 2453 | Slovenia | SVN | 2020 | 1.237830e+04 |
| 2454 | Slovenia | SVN | 2019 | 1.239860e+04 |
| 2455 | Slovenia | SVN | 2018 | 1.241900e+04 |
| 2456 | Slovenia | SVN | 2017 | 1.243930e+04 |
| 2457 | Slovenia | SVN | 2016 | 1.245970e+04 |
| 2458 | Slovenia | SVN | 2015 | 1.248000e+04 |
| 2459 | Slovenia | SVN | 2014 | 1.247800e+04 |
| 2460 | Slovenia | SVN | 2013 | 1.247600e+04 |
| 2461 | Slovenia | SVN | 2012 | 1.247400e+04 |
| 2462 | Slovenia | SVN | 2011 | 1.247200e+04 |
| 2463 | Slovenia | SVN | 2010 | 1.247000e+04 |
| 2464 | Solomon Islands | SLB | 2020 | 2.522970e+04 |
| 2465 | Solomon Islands | SLB | 2019 | 2.523700e+04 |
| 2466 | Solomon Islands | SLB | 2018 | 2.524430e+04 |
| 2467 | Solomon Islands | SLB | 2017 | 2.525160e+04 |
| 2468 | Solomon Islands | SLB | 2016 | 2.525890e+04 |
| 2469 | Solomon Islands | SLB | 2015 | 2.526620e+04 |
| 2470 | Solomon Islands | SLB | 2014 | 2.527352e+04 |
| 2471 | Solomon Islands | SLB | 2013 | 2.528084e+04 |
| 2472 | Solomon Islands | SLB | 2012 | 2.528816e+04 |
| 2473 | Solomon Islands | SLB | 2011 | 2.529548e+04 |
| 2474 | Solomon Islands | SLB | 2010 | 2.530280e+04 |
| 2475 | Somalia | SOM | 2020 | 5.980000e+04 |
| 2476 | Somalia | SOM | 2019 | 6.056750e+04 |
| 2477 | Somalia | SOM | 2018 | 6.133500e+04 |
| 2478 | Somalia | SOM | 2017 | 6.210250e+04 |
| 2479 | Somalia | SOM | 2016 | 6.287000e+04 |
| 2480 | Somalia | SOM | 2015 | 6.363750e+04 |
| 2481 | Somalia | SOM | 2014 | 6.440500e+04 |
| 2482 | Somalia | SOM | 2013 | 6.517250e+04 |
| 2483 | Somalia | SOM | 2012 | 6.594000e+04 |
| 2484 | Somalia | SOM | 2011 | 6.670750e+04 |
| 2485 | Somalia | SOM | 2010 | 6.747500e+04 |
| 2486 | South Africa | ZAF | 2020 | 1.705009e+05 |
| 2487 | South Africa | ZAF | 2019 | 1.708649e+05 |
| 2488 | South Africa | ZAF | 2018 | 1.712289e+05 |
| 2489 | South Africa | ZAF | 2017 | 1.715929e+05 |
| 2490 | South Africa | ZAF | 2016 | 1.719569e+05 |
| 2491 | South Africa | ZAF | 2015 | 1.723209e+05 |
| 2492 | South Africa | ZAF | 2014 | 1.726849e+05 |
| 2493 | South Africa | ZAF | 2013 | 1.730489e+05 |
| 2494 | South Africa | ZAF | 2012 | 1.734129e+05 |
| 2495 | South Africa | ZAF | 2011 | 1.737769e+05 |
| 2496 | South Africa | ZAF | 2010 | 1.741409e+05 |
| 2497 | South Sudan | SSD | 2020 | 7.157000e+04 |
| 2498 | South Sudan | SSD | 2019 | 7.157000e+04 |
| 2499 | South Sudan | SSD | 2018 | 7.157000e+04 |
| 2500 | South Sudan | SSD | 2017 | 7.157000e+04 |
| 2501 | South Sudan | SSD | 2016 | 7.157000e+04 |
| 2502 | South Sudan | SSD | 2015 | 7.157000e+04 |
| 2503 | South Sudan | SSD | 2014 | 7.157000e+04 |
| 2504 | South Sudan | SSD | 2013 | 7.157000e+04 |
| 2505 | South Sudan | SSD | 2012 | 7.157000e+04 |
| 2506 | South Sudan | SSD | 2011 | NaN |
| 2507 | South Sudan | SSD | 2010 | NaN |
| 2508 | Spain | ESP | 2020 | 1.857217e+05 |
| 2509 | Spain | ESP | 2019 | 1.856788e+05 |
| 2510 | Spain | ESP | 2018 | 1.856359e+05 |
| 2511 | Spain | ESP | 2017 | 1.855930e+05 |
| 2512 | Spain | ESP | 2016 | 1.855524e+05 |
| 2513 | Spain | ESP | 2015 | 1.855118e+05 |
| 2514 | Spain | ESP | 2014 | 1.855001e+05 |
| 2515 | Spain | ESP | 2013 | 1.854884e+05 |
| 2516 | Spain | ESP | 2012 | 1.854768e+05 |
| 2517 | Spain | ESP | 2011 | 1.854651e+05 |
| 2518 | Spain | ESP | 2010 | 1.854534e+05 |
| 2519 | Sri Lanka | LKA | 2020 | 2.113020e+04 |
| 2520 | Sri Lanka | LKA | 2019 | 2.116180e+04 |
| 2521 | Sri Lanka | LKA | 2018 | 2.119340e+04 |
| 2522 | Sri Lanka | LKA | 2017 | 2.122500e+04 |
| 2523 | Sri Lanka | LKA | 2016 | 2.125660e+04 |
| 2524 | Sri Lanka | LKA | 2015 | 2.128820e+04 |
| 2525 | Sri Lanka | LKA | 2014 | 2.123780e+04 |
| 2526 | Sri Lanka | LKA | 2013 | 2.118740e+04 |
| 2527 | Sri Lanka | LKA | 2012 | 2.113700e+04 |
| 2528 | Sri Lanka | LKA | 2011 | 2.108660e+04 |
| 2529 | Sri Lanka | LKA | 2010 | 2.103620e+04 |
| 2530 | St. Kitts and Nevis | KNA | 2020 | 1.100000e+02 |
| 2531 | St. Kitts and Nevis | KNA | 2019 | 1.100000e+02 |
| 2532 | St. Kitts and Nevis | KNA | 2018 | 1.100000e+02 |
| 2533 | St. Kitts and Nevis | KNA | 2017 | 1.100000e+02 |
| 2534 | St. Kitts and Nevis | KNA | 2016 | 1.100000e+02 |
| 2535 | St. Kitts and Nevis | KNA | 2015 | 1.100000e+02 |
| 2536 | St. Kitts and Nevis | KNA | 2014 | 1.100000e+02 |
| 2537 | St. Kitts and Nevis | KNA | 2013 | 1.100000e+02 |
| 2538 | St. Kitts and Nevis | KNA | 2012 | 1.100000e+02 |
| 2539 | St. Kitts and Nevis | KNA | 2011 | 1.100000e+02 |
| 2540 | St. Kitts and Nevis | KNA | 2010 | 1.100000e+02 |
| 2541 | St. Lucia | LCA | 2020 | 2.077000e+02 |
| 2542 | St. Lucia | LCA | 2019 | 2.077000e+02 |
| 2543 | St. Lucia | LCA | 2018 | 2.077000e+02 |
| 2544 | St. Lucia | LCA | 2017 | 2.077000e+02 |
| 2545 | St. Lucia | LCA | 2016 | 2.077000e+02 |
| 2546 | St. Lucia | LCA | 2015 | 2.077000e+02 |
| 2547 | St. Lucia | LCA | 2014 | 2.077000e+02 |
| 2548 | St. Lucia | LCA | 2013 | 2.077000e+02 |
| 2549 | St. Lucia | LCA | 2012 | 2.077000e+02 |
| 2550 | St. Lucia | LCA | 2011 | 2.077000e+02 |
| 2551 | St. Lucia | LCA | 2010 | 2.077000e+02 |
| 2552 | St. Martin (French part) | MAF | 2020 | 1.240000e+01 |
| 2553 | St. Martin (French part) | MAF | 2019 | 1.240000e+01 |
| 2554 | St. Martin (French part) | MAF | 2018 | 1.240000e+01 |
| 2555 | St. Martin (French part) | MAF | 2017 | 1.240000e+01 |
| 2556 | St. Martin (French part) | MAF | 2016 | 1.240000e+01 |
| 2557 | St. Martin (French part) | MAF | 2015 | 1.240000e+01 |
| 2558 | St. Martin (French part) | MAF | 2014 | 1.240000e+01 |
| 2559 | St. Martin (French part) | MAF | 2013 | 1.240000e+01 |
| 2560 | St. Martin (French part) | MAF | 2012 | 1.240000e+01 |
| 2561 | St. Martin (French part) | MAF | 2011 | 1.240000e+01 |
| 2562 | St. Martin (French part) | MAF | 2010 | NaN |
| 2563 | St. Vincent and the Grenadines | VCT | 2020 | 2.854000e+02 |
| 2564 | St. Vincent and the Grenadines | VCT | 2019 | 2.854000e+02 |
| 2565 | St. Vincent and the Grenadines | VCT | 2018 | 2.854000e+02 |
| 2566 | St. Vincent and the Grenadines | VCT | 2017 | 2.854000e+02 |
| 2567 | St. Vincent and the Grenadines | VCT | 2016 | 2.854000e+02 |
| 2568 | St. Vincent and the Grenadines | VCT | 2015 | 2.854000e+02 |
| 2569 | St. Vincent and the Grenadines | VCT | 2014 | 2.854000e+02 |
| 2570 | St. Vincent and the Grenadines | VCT | 2013 | 2.854000e+02 |
| 2571 | St. Vincent and the Grenadines | VCT | 2012 | 2.854000e+02 |
| 2572 | St. Vincent and the Grenadines | VCT | 2011 | 2.854000e+02 |
| 2573 | St. Vincent and the Grenadines | VCT | 2010 | 2.854000e+02 |
| 2574 | Sudan | SDN | 2020 | 1.835955e+05 |
| 2575 | Sudan | SDN | 2019 | 1.853171e+05 |
| 2576 | Sudan | SDN | 2018 | 1.870387e+05 |
| 2577 | Sudan | SDN | 2017 | 1.887603e+05 |
| 2578 | Sudan | SDN | 2016 | 1.904819e+05 |
| 2579 | Sudan | SDN | 2015 | 1.920993e+05 |
| 2580 | Sudan | SDN | 2014 | 1.938418e+05 |
| 2581 | Sudan | SDN | 2013 | 1.955843e+05 |
| 2582 | Sudan | SDN | 2012 | 1.973267e+05 |
| 2583 | Sudan | SDN | 2011 | 2.706392e+05 |
| 2584 | Sudan | SDN | 2010 | 2.723817e+05 |
| 2585 | Suriname | SUR | 2020 | 1.519629e+05 |
| 2586 | Suriname | SUR | 2019 | 1.520853e+05 |
| 2587 | Suriname | SUR | 2018 | 1.522078e+05 |
| 2588 | Suriname | SUR | 2017 | 1.523302e+05 |
| 2589 | Suriname | SUR | 2016 | 1.524032e+05 |
| 2590 | Suriname | SUR | 2015 | 1.525167e+05 |
| 2591 | Suriname | SUR | 2014 | 1.526131e+05 |
| 2592 | Suriname | SUR | 2013 | 1.527095e+05 |
| 2593 | Suriname | SUR | 2012 | 1.528058e+05 |
| 2594 | Suriname | SUR | 2011 | 1.529022e+05 |
| 2595 | Suriname | SUR | 2010 | 1.529986e+05 |
| 2596 | Sweden | SWE | 2020 | 2.798000e+05 |
| 2597 | Sweden | SWE | 2019 | 2.798000e+05 |
| 2598 | Sweden | SWE | 2018 | 2.798000e+05 |
| 2599 | Sweden | SWE | 2017 | 2.798000e+05 |
| 2600 | Sweden | SWE | 2016 | 2.798000e+05 |
| 2601 | Sweden | SWE | 2015 | 2.798000e+05 |
| 2602 | Sweden | SWE | 2014 | 2.799860e+05 |
| 2603 | Sweden | SWE | 2013 | 2.801720e+05 |
| 2604 | Sweden | SWE | 2012 | 2.803580e+05 |
| 2605 | Sweden | SWE | 2011 | 2.805440e+05 |
| 2606 | Sweden | SWE | 2010 | 2.807300e+05 |
| 2607 | Switzerland | CHE | 2020 | 1.269110e+04 |
| 2608 | Switzerland | CHE | 2019 | 1.265670e+04 |
| 2609 | Switzerland | CHE | 2018 | 1.262230e+04 |
| 2610 | Switzerland | CHE | 2017 | 1.258790e+04 |
| 2611 | Switzerland | CHE | 2016 | 1.255350e+04 |
| 2612 | Switzerland | CHE | 2015 | 1.251910e+04 |
| 2613 | Switzerland | CHE | 2014 | 1.248472e+04 |
| 2614 | Switzerland | CHE | 2013 | 1.245034e+04 |
| 2615 | Switzerland | CHE | 2012 | 1.241596e+04 |
| 2616 | Switzerland | CHE | 2011 | 1.238158e+04 |
| 2617 | Switzerland | CHE | 2010 | 1.234720e+04 |
| 2618 | Syrian Arab Republic | SYR | 2020 | 5.220800e+03 |
| 2619 | Syrian Arab Republic | SYR | 2019 | 5.220800e+03 |
| 2620 | Syrian Arab Republic | SYR | 2018 | 5.220800e+03 |
| 2621 | Syrian Arab Republic | SYR | 2017 | 5.220800e+03 |
| 2622 | Syrian Arab Republic | SYR | 2016 | 5.220800e+03 |
| 2623 | Syrian Arab Republic | SYR | 2015 | 5.220800e+03 |
| 2624 | Syrian Arab Republic | SYR | 2014 | 5.160800e+03 |
| 2625 | Syrian Arab Republic | SYR | 2013 | 5.100800e+03 |
| 2626 | Syrian Arab Republic | SYR | 2012 | 5.040800e+03 |
| 2627 | Syrian Arab Republic | SYR | 2011 | 4.980800e+03 |
| 2628 | Syrian Arab Republic | SYR | 2010 | 4.920800e+03 |
| 2629 | Tajikistan | TJK | 2020 | 4.238000e+03 |
| 2630 | Tajikistan | TJK | 2019 | 4.228000e+03 |
| 2631 | Tajikistan | TJK | 2018 | 4.218000e+03 |
| 2632 | Tajikistan | TJK | 2017 | 4.218000e+03 |
| 2633 | Tajikistan | TJK | 2016 | 4.218000e+03 |
| 2634 | Tajikistan | TJK | 2015 | 4.218000e+03 |
| 2635 | Tajikistan | TJK | 2014 | 4.194400e+03 |
| 2636 | Tajikistan | TJK | 2013 | 4.170800e+03 |
| 2637 | Tajikistan | TJK | 2012 | 4.147200e+03 |
| 2638 | Tajikistan | TJK | 2011 | 4.123600e+03 |
| 2639 | Tajikistan | TJK | 2010 | 4.100000e+03 |
| 2640 | Tanzania | TZA | 2020 | 4.574500e+05 |
| 2641 | Tanzania | TZA | 2019 | 4.621400e+05 |
| 2642 | Tanzania | TZA | 2018 | 4.668300e+05 |
| 2643 | Tanzania | TZA | 2017 | 4.715200e+05 |
| 2644 | Tanzania | TZA | 2016 | 4.762100e+05 |
| 2645 | Tanzania | TZA | 2015 | 4.809000e+05 |
| 2646 | Tanzania | TZA | 2014 | 4.846200e+05 |
| 2647 | Tanzania | TZA | 2013 | 4.883400e+05 |
| 2648 | Tanzania | TZA | 2012 | 4.920601e+05 |
| 2649 | Tanzania | TZA | 2011 | 4.957801e+05 |
| 2650 | Tanzania | TZA | 2010 | 4.995001e+05 |
| 2651 | Thailand | THA | 2020 | 1.987300e+05 |
| 2652 | Thailand | THA | 2019 | 1.990900e+05 |
| 2653 | Thailand | THA | 2018 | 1.994500e+05 |
| 2654 | Thailand | THA | 2017 | 1.998100e+05 |
| 2655 | Thailand | THA | 2016 | 2.001700e+05 |
| 2656 | Thailand | THA | 2015 | 2.006100e+05 |
| 2657 | Thailand | THA | 2014 | 2.006340e+05 |
| 2658 | Thailand | THA | 2013 | 2.006580e+05 |
| 2659 | Thailand | THA | 2012 | 2.006820e+05 |
| 2660 | Thailand | THA | 2011 | 2.007060e+05 |
| 2661 | Thailand | THA | 2010 | 2.007300e+05 |
| 2662 | Timor-Leste | TLS | 2020 | 9.211000e+03 |
| 2663 | Timor-Leste | TLS | 2019 | 9.225000e+03 |
| 2664 | Timor-Leste | TLS | 2018 | 9.239000e+03 |
| 2665 | Timor-Leste | TLS | 2017 | 9.256000e+03 |
| 2666 | Timor-Leste | TLS | 2016 | 9.267000e+03 |
| 2667 | Timor-Leste | TLS | 2015 | 9.281000e+03 |
| 2668 | Timor-Leste | TLS | 2014 | 9.295000e+03 |
| 2669 | Timor-Leste | TLS | 2013 | 9.309000e+03 |
| 2670 | Timor-Leste | TLS | 2012 | 9.323000e+03 |
| 2671 | Timor-Leste | TLS | 2011 | 9.337000e+03 |
| 2672 | Timor-Leste | TLS | 2010 | 9.351000e+03 |
| 2673 | Togo | TGO | 2020 | 1.209270e+04 |
| 2674 | Togo | TGO | 2019 | 1.212230e+04 |
| 2675 | Togo | TGO | 2018 | 1.215190e+04 |
| 2676 | Togo | TGO | 2017 | 1.218150e+04 |
| 2677 | Togo | TGO | 2016 | 1.221110e+04 |
| 2678 | Togo | TGO | 2015 | 1.224070e+04 |
| 2679 | Togo | TGO | 2014 | 1.227030e+04 |
| 2680 | Togo | TGO | 2013 | 1.229990e+04 |
| 2681 | Togo | TGO | 2012 | 1.232950e+04 |
| 2682 | Togo | TGO | 2011 | 1.235910e+04 |
| 2683 | Togo | TGO | 2010 | 1.238870e+04 |
| 2684 | Tonga | TON | 2020 | 8.950000e+01 |
| 2685 | Tonga | TON | 2019 | 8.950000e+01 |
| 2686 | Tonga | TON | 2018 | 8.950000e+01 |
| 2687 | Tonga | TON | 2017 | 8.950000e+01 |
| 2688 | Tonga | TON | 2016 | 8.950000e+01 |
| 2689 | Tonga | TON | 2015 | 8.950000e+01 |
| 2690 | Tonga | TON | 2014 | 8.950000e+01 |
| 2691 | Tonga | TON | 2013 | 8.950000e+01 |
| 2692 | Tonga | TON | 2012 | 8.950000e+01 |
| 2693 | Tonga | TON | 2011 | 8.950000e+01 |
| 2694 | Tonga | TON | 2010 | 8.950000e+01 |
| 2695 | Trinidad and Tobago | TTO | 2020 | 2.281900e+03 |
| 2696 | Trinidad and Tobago | TTO | 2019 | 2.286100e+03 |
| 2697 | Trinidad and Tobago | TTO | 2018 | 2.290300e+03 |
| 2698 | Trinidad and Tobago | TTO | 2017 | 2.294500e+03 |
| 2699 | Trinidad and Tobago | TTO | 2016 | 2.298700e+03 |
| 2700 | Trinidad and Tobago | TTO | 2015 | 2.302900e+03 |
| 2701 | Trinidad and Tobago | TTO | 2014 | 2.307140e+03 |
| 2702 | Trinidad and Tobago | TTO | 2013 | 2.311380e+03 |
| 2703 | Trinidad and Tobago | TTO | 2012 | 2.315620e+03 |
| 2704 | Trinidad and Tobago | TTO | 2011 | 2.319860e+03 |
| 2705 | Trinidad and Tobago | TTO | 2010 | 2.324100e+03 |
| 2706 | Tunisia | TUN | 2020 | 7.027300e+03 |
| 2707 | Tunisia | TUN | 2019 | 7.012000e+03 |
| 2708 | Tunisia | TUN | 2018 | 6.996700e+03 |
| 2709 | Tunisia | TUN | 2017 | 6.981400e+03 |
| 2710 | Tunisia | TUN | 2016 | 6.966100e+03 |
| 2711 | Tunisia | TUN | 2015 | 6.950800e+03 |
| 2712 | Tunisia | TUN | 2014 | 6.935500e+03 |
| 2713 | Tunisia | TUN | 2013 | 6.920200e+03 |
| 2714 | Tunisia | TUN | 2012 | 6.904900e+03 |
| 2715 | Tunisia | TUN | 2011 | 6.889600e+03 |
| 2716 | Tunisia | TUN | 2010 | 6.874300e+03 |
| 2717 | Turkiye | TUR | 2020 | 2.222036e+05 |
| 2718 | Turkiye | TUR | 2019 | 2.206436e+05 |
| 2719 | Turkiye | TUR | 2018 | 2.190836e+05 |
| 2720 | Turkiye | TUR | 2017 | 2.175246e+05 |
| 2721 | Turkiye | TUR | 2016 | 2.163030e+05 |
| 2722 | Turkiye | TUR | 2015 | 2.163030e+05 |
| 2723 | Turkiye | TUR | 2014 | 2.152086e+05 |
| 2724 | Turkiye | TUR | 2013 | 2.141141e+05 |
| 2725 | Turkiye | TUR | 2012 | 2.130197e+05 |
| 2726 | Turkiye | TUR | 2011 | 2.119252e+05 |
| 2727 | Turkiye | TUR | 2010 | 2.108308e+05 |
| 2728 | Turkmenistan | TKM | 2020 | 4.127000e+04 |
| 2729 | Turkmenistan | TKM | 2019 | 4.127000e+04 |
| 2730 | Turkmenistan | TKM | 2018 | 4.127000e+04 |
| 2731 | Turkmenistan | TKM | 2017 | 4.127000e+04 |
| 2732 | Turkmenistan | TKM | 2016 | 4.127000e+04 |
| 2733 | Turkmenistan | TKM | 2015 | 4.127000e+04 |
| 2734 | Turkmenistan | TKM | 2014 | 4.127000e+04 |
| 2735 | Turkmenistan | TKM | 2013 | 4.127000e+04 |
| 2736 | Turkmenistan | TKM | 2012 | 4.127000e+04 |
| 2737 | Turkmenistan | TKM | 2011 | 4.127000e+04 |
| 2738 | Turkmenistan | TKM | 2010 | 4.127000e+04 |
| 2739 | Turks and Caicos Islands | TCA | 2020 | 1.052000e+02 |
| 2740 | Turks and Caicos Islands | TCA | 2019 | 1.052000e+02 |
| 2741 | Turks and Caicos Islands | TCA | 2018 | 1.052000e+02 |
| 2742 | Turks and Caicos Islands | TCA | 2017 | 1.052000e+02 |
| 2743 | Turks and Caicos Islands | TCA | 2016 | 1.052000e+02 |
| 2744 | Turks and Caicos Islands | TCA | 2015 | 1.052000e+02 |
| 2745 | Turks and Caicos Islands | TCA | 2014 | 1.052000e+02 |
| 2746 | Turks and Caicos Islands | TCA | 2013 | 1.052000e+02 |
| 2747 | Turks and Caicos Islands | TCA | 2012 | 1.052000e+02 |
| 2748 | Turks and Caicos Islands | TCA | 2011 | 1.052000e+02 |
| 2749 | Turks and Caicos Islands | TCA | 2010 | 1.052000e+02 |
| 2750 | Tuvalu | TUV | 2020 | 1.000000e+01 |
| 2751 | Tuvalu | TUV | 2019 | 1.000000e+01 |
| 2752 | Tuvalu | TUV | 2018 | 1.000000e+01 |
| 2753 | Tuvalu | TUV | 2017 | 1.000000e+01 |
| 2754 | Tuvalu | TUV | 2016 | 1.000000e+01 |
| 2755 | Tuvalu | TUV | 2015 | 1.000000e+01 |
| 2756 | Tuvalu | TUV | 2014 | 1.000000e+01 |
| 2757 | Tuvalu | TUV | 2013 | 1.000000e+01 |
| 2758 | Tuvalu | TUV | 2012 | 1.000000e+01 |
| 2759 | Tuvalu | TUV | 2011 | 1.000000e+01 |
| 2760 | Tuvalu | TUV | 2010 | 1.000000e+01 |
| 2761 | Uganda | UGA | 2020 | 2.337900e+04 |
| 2762 | Uganda | UGA | 2019 | 2.379150e+04 |
| 2763 | Uganda | UGA | 2018 | 2.420410e+04 |
| 2764 | Uganda | UGA | 2017 | 2.461660e+04 |
| 2765 | Uganda | UGA | 2016 | 2.502910e+04 |
| 2766 | Uganda | UGA | 2015 | 2.544160e+04 |
| 2767 | Uganda | UGA | 2014 | 2.585412e+04 |
| 2768 | Uganda | UGA | 2013 | 2.626664e+04 |
| 2769 | Uganda | UGA | 2012 | 2.667916e+04 |
| 2770 | Uganda | UGA | 2011 | 2.709168e+04 |
| 2771 | Uganda | UGA | 2010 | 2.750420e+04 |
| 2772 | Ukraine | UKR | 2020 | 9.690000e+04 |
| 2773 | Ukraine | UKR | 2019 | 9.684000e+04 |
| 2774 | Ukraine | UKR | 2018 | 9.678000e+04 |
| 2775 | Ukraine | UKR | 2017 | 9.671000e+04 |
| 2776 | Ukraine | UKR | 2016 | 9.664000e+04 |
| 2777 | Ukraine | UKR | 2015 | 9.657000e+04 |
| 2778 | Ukraine | UKR | 2014 | 9.635200e+04 |
| 2779 | Ukraine | UKR | 2013 | 9.613400e+04 |
| 2780 | Ukraine | UKR | 2012 | 9.591600e+04 |
| 2781 | Ukraine | UKR | 2011 | 9.569800e+04 |
| 2782 | Ukraine | UKR | 2010 | 9.548000e+04 |
| 2783 | United Arab Emirates | ARE | 2020 | 3.173000e+03 |
| 2784 | United Arab Emirates | ARE | 2019 | 3.173000e+03 |
| 2785 | United Arab Emirates | ARE | 2018 | 3.173000e+03 |
| 2786 | United Arab Emirates | ARE | 2017 | 3.173000e+03 |
| 2787 | United Arab Emirates | ARE | 2016 | 3.173000e+03 |
| 2788 | United Arab Emirates | ARE | 2015 | 3.173000e+03 |
| 2789 | United Arab Emirates | ARE | 2014 | 3.173000e+03 |
| 2790 | United Arab Emirates | ARE | 2013 | 3.173000e+03 |
| 2791 | United Arab Emirates | ARE | 2012 | 3.173000e+03 |
| 2792 | United Arab Emirates | ARE | 2011 | 3.173000e+03 |
| 2793 | United Arab Emirates | ARE | 2010 | 3.173000e+03 |
| 2794 | United Kingdom | GBR | 2020 | 3.190000e+04 |
| 2795 | United Kingdom | GBR | 2019 | 3.182000e+04 |
| 2796 | United Kingdom | GBR | 2018 | 3.173000e+04 |
| 2797 | United Kingdom | GBR | 2017 | 3.164000e+04 |
| 2798 | United Kingdom | GBR | 2016 | 3.159000e+04 |
| 2799 | United Kingdom | GBR | 2015 | 3.155000e+04 |
| 2800 | United Kingdom | GBR | 2014 | 3.135800e+04 |
| 2801 | United Kingdom | GBR | 2013 | 3.116600e+04 |
| 2802 | United Kingdom | GBR | 2012 | 3.097400e+04 |
| 2803 | United Kingdom | GBR | 2011 | 3.078200e+04 |
| 2804 | United Kingdom | GBR | 2010 | 3.059000e+04 |
| 2805 | United States | USA | 2020 | 3.097950e+06 |
| 2806 | United States | USA | 2019 | 3.097950e+06 |
| 2807 | United States | USA | 2018 | 3.097950e+06 |
| 2808 | United States | USA | 2017 | 3.097950e+06 |
| 2809 | United States | USA | 2016 | 3.100950e+06 |
| 2810 | United States | USA | 2015 | 3.100950e+06 |
| 2811 | United States | USA | 2014 | 3.098200e+06 |
| 2812 | United States | USA | 2013 | 3.095450e+06 |
| 2813 | United States | USA | 2012 | 3.092700e+06 |
| 2814 | United States | USA | 2011 | 3.089950e+06 |
| 2815 | United States | USA | 2010 | 3.087200e+06 |
| 2816 | Uruguay | URY | 2020 | 2.031000e+04 |
| 2817 | Uruguay | URY | 2019 | 2.010000e+04 |
| 2818 | Uruguay | URY | 2018 | 1.989000e+04 |
| 2819 | Uruguay | URY | 2017 | 1.968000e+04 |
| 2820 | Uruguay | URY | 2016 | 1.947000e+04 |
| 2821 | Uruguay | URY | 2015 | 1.920000e+04 |
| 2822 | Uruguay | URY | 2014 | 1.882260e+04 |
| 2823 | Uruguay | URY | 2013 | 1.844520e+04 |
| 2824 | Uruguay | URY | 2012 | 1.806780e+04 |
| 2825 | Uruguay | URY | 2011 | 1.769040e+04 |
| 2826 | Uruguay | URY | 2010 | 1.731300e+04 |
| 2827 | Uzbekistan | UZB | 2020 | 3.689660e+04 |
| 2828 | Uzbekistan | UZB | 2019 | 3.663820e+04 |
| 2829 | Uzbekistan | UZB | 2018 | 3.637980e+04 |
| 2830 | Uzbekistan | UZB | 2017 | 3.612136e+04 |
| 2831 | Uzbekistan | UZB | 2016 | 3.586300e+04 |
| 2832 | Uzbekistan | UZB | 2015 | 3.549400e+04 |
| 2833 | Uzbekistan | UZB | 2014 | 3.509440e+04 |
| 2834 | Uzbekistan | UZB | 2013 | 3.469480e+04 |
| 2835 | Uzbekistan | UZB | 2012 | 3.429520e+04 |
| 2836 | Uzbekistan | UZB | 2011 | 3.389560e+04 |
| 2837 | Uzbekistan | UZB | 2010 | 3.349600e+04 |
| 2838 | Vanuatu | VUT | 2020 | 4.423000e+03 |
| 2839 | Vanuatu | VUT | 2019 | 4.423000e+03 |
| 2840 | Vanuatu | VUT | 2018 | 4.423000e+03 |
| 2841 | Vanuatu | VUT | 2017 | 4.423000e+03 |
| 2842 | Vanuatu | VUT | 2016 | 4.423000e+03 |
| 2843 | Vanuatu | VUT | 2015 | 4.423000e+03 |
| 2844 | Vanuatu | VUT | 2014 | 4.423000e+03 |
| 2845 | Vanuatu | VUT | 2013 | 4.423000e+03 |
| 2846 | Vanuatu | VUT | 2012 | 4.423000e+03 |
| 2847 | Vanuatu | VUT | 2011 | 4.423000e+03 |
| 2848 | Vanuatu | VUT | 2010 | 4.423000e+03 |
| 2849 | Venezuela, RB | VEN | 2020 | 4.623090e+05 |
| 2850 | Venezuela, RB | VEN | 2019 | 4.627200e+05 |
| 2851 | Venezuela, RB | VEN | 2018 | 4.633776e+05 |
| 2852 | Venezuela, RB | VEN | 2017 | 4.642818e+05 |
| 2853 | Venezuela, RB | VEN | 2016 | 4.654326e+05 |
| 2854 | Venezuela, RB | VEN | 2015 | 4.668300e+05 |
| 2855 | Venezuela, RB | VEN | 2014 | 4.684740e+05 |
| 2856 | Venezuela, RB | VEN | 2013 | 4.701180e+05 |
| 2857 | Venezuela, RB | VEN | 2012 | 4.717620e+05 |
| 2858 | Venezuela, RB | VEN | 2011 | 4.734060e+05 |
| 2859 | Venezuela, RB | VEN | 2010 | 4.750500e+05 |
| 2860 | Viet Nam | VNM | 2020 | 1.464309e+05 |
| 2861 | Viet Nam | VNM | 2019 | 1.456719e+05 |
| 2862 | Viet Nam | VNM | 2018 | 1.449129e+05 |
| 2863 | Viet Nam | VNM | 2017 | 1.441539e+05 |
| 2864 | Viet Nam | VNM | 2016 | 1.437768e+05 |
| 2865 | Viet Nam | VNM | 2015 | 1.406186e+05 |
| 2866 | Viet Nam | VNM | 2014 | 1.392710e+05 |
| 2867 | Viet Nam | VNM | 2013 | 1.379234e+05 |
| 2868 | Viet Nam | VNM | 2012 | 1.365758e+05 |
| 2869 | Viet Nam | VNM | 2011 | 1.352282e+05 |
| 2870 | Viet Nam | VNM | 2010 | 1.338806e+05 |
| 2871 | Virgin Islands (U.S.) | VIR | 2020 | 1.991000e+02 |
| 2872 | Virgin Islands (U.S.) | VIR | 2019 | 1.976000e+02 |
| 2873 | Virgin Islands (U.S.) | VIR | 2018 | 1.961000e+02 |
| 2874 | Virgin Islands (U.S.) | VIR | 2017 | 1.946000e+02 |
| 2875 | Virgin Islands (U.S.) | VIR | 2016 | 1.931000e+02 |
| 2876 | Virgin Islands (U.S.) | VIR | 2015 | 1.916000e+02 |
| 2877 | Virgin Islands (U.S.) | VIR | 2014 | 1.901400e+02 |
| 2878 | Virgin Islands (U.S.) | VIR | 2013 | 1.886800e+02 |
| 2879 | Virgin Islands (U.S.) | VIR | 2012 | 1.872200e+02 |
| 2880 | Virgin Islands (U.S.) | VIR | 2011 | 1.857600e+02 |
| 2881 | Virgin Islands (U.S.) | VIR | 2010 | 1.843000e+02 |
| 2882 | West Bank and Gaza | PSE | 2020 | 1.014000e+02 |
| 2883 | West Bank and Gaza | PSE | 2019 | 1.014000e+02 |
| 2884 | West Bank and Gaza | PSE | 2018 | 1.014000e+02 |
| 2885 | West Bank and Gaza | PSE | 2017 | 1.014000e+02 |
| 2886 | West Bank and Gaza | PSE | 2016 | 1.014000e+02 |
| 2887 | West Bank and Gaza | PSE | 2015 | 1.014000e+02 |
| 2888 | West Bank and Gaza | PSE | 2014 | 1.010200e+02 |
| 2889 | West Bank and Gaza | PSE | 2013 | 1.006400e+02 |
| 2890 | West Bank and Gaza | PSE | 2012 | 1.002600e+02 |
| 2891 | West Bank and Gaza | PSE | 2011 | 9.988000e+01 |
| 2892 | West Bank and Gaza | PSE | 2010 | 9.950000e+01 |
| 2893 | Yemen, Rep. | YEM | 2020 | 5.490000e+03 |
| 2894 | Yemen, Rep. | YEM | 2019 | 5.490000e+03 |
| 2895 | Yemen, Rep. | YEM | 2018 | 5.490000e+03 |
| 2896 | Yemen, Rep. | YEM | 2017 | 5.490000e+03 |
| 2897 | Yemen, Rep. | YEM | 2016 | 5.490000e+03 |
| 2898 | Yemen, Rep. | YEM | 2015 | 5.490000e+03 |
| 2899 | Yemen, Rep. | YEM | 2014 | 5.490000e+03 |
| 2900 | Yemen, Rep. | YEM | 2013 | 5.490000e+03 |
| 2901 | Yemen, Rep. | YEM | 2012 | 5.490000e+03 |
| 2902 | Yemen, Rep. | YEM | 2011 | 5.490000e+03 |
| 2903 | Yemen, Rep. | YEM | 2010 | 5.490000e+03 |
| 2904 | Zambia | ZMB | 2020 | 4.481403e+05 |
| 2905 | Zambia | ZMB | 2019 | 4.500224e+05 |
| 2906 | Zambia | ZMB | 2018 | 4.519046e+05 |
| 2907 | Zambia | ZMB | 2017 | 4.537867e+05 |
| 2908 | Zambia | ZMB | 2016 | 4.556680e+05 |
| 2909 | Zambia | ZMB | 2015 | 4.575510e+05 |
| 2910 | Zambia | ZMB | 2014 | 4.594328e+05 |
| 2911 | Zambia | ZMB | 2013 | 4.613146e+05 |
| 2912 | Zambia | ZMB | 2012 | 4.631964e+05 |
| 2913 | Zambia | ZMB | 2011 | 4.650782e+05 |
| 2914 | Zambia | ZMB | 2010 | 4.669600e+05 |
| 2915 | Zimbabwe | ZWE | 2020 | 1.744458e+05 |
| 2916 | Zimbabwe | ZWE | 2019 | 1.749065e+05 |
| 2917 | Zimbabwe | ZWE | 2018 | 1.753672e+05 |
| 2918 | Zimbabwe | ZWE | 2017 | 1.758279e+05 |
| 2919 | Zimbabwe | ZWE | 2016 | 1.762886e+05 |
| 2920 | Zimbabwe | ZWE | 2015 | 1.767493e+05 |
| 2921 | Zimbabwe | ZWE | 2014 | 1.772100e+05 |
| 2922 | Zimbabwe | ZWE | 2013 | 1.776707e+05 |
| 2923 | Zimbabwe | ZWE | 2012 | 1.781314e+05 |
| 2924 | Zimbabwe | ZWE | 2011 | 1.785921e+05 |
| 2925 | Zimbabwe | ZWE | 2010 | 1.790528e+05 |
worldbank_forest = pd.DataFrame(worldbank_forest)
excel_worldbank_forest = "worldbank_forest.xlsx"
worldbank_forest.to_excel(excel_worldbank_forest, index=False)
indicator = 'SP.POP.TOTL?date=2010:2020'
url = "http://api.worldbank.org/v2/countries/all/indicators/%s&format=json&per_page=5000" % indicator
response = requests.get(url)
result = response.content
result = json.loads(result)
worldbank_population = pd.DataFrame.from_dict(result[1])
worldbank_population ['country'] = worldbank_population [['country']].applymap(lambda x : x['value'])
worldbank_population
worldbank_population .country.unique()
worldbank_population = worldbank_population [['country', 'countryiso3code', 'date', 'value']]
worldbank_population .columns = ['Country_name', 'Countrycode', 'year', 'Population']
worldbank_population
| Country_name | Countrycode | year | Population | |
|---|---|---|---|---|
| 0 | Africa Eastern and Southern | AFE | 2020 | 6.851130e+08 |
| 1 | Africa Eastern and Southern | AFE | 2019 | 6.672430e+08 |
| 2 | Africa Eastern and Southern | AFE | 2018 | 6.497571e+08 |
| 3 | Africa Eastern and Southern | AFE | 2017 | 6.327466e+08 |
| 4 | Africa Eastern and Southern | AFE | 2016 | 6.163776e+08 |
| 5 | Africa Eastern and Southern | AFE | 2015 | 6.000084e+08 |
| 6 | Africa Eastern and Southern | AFE | 2014 | 5.836511e+08 |
| 7 | Africa Eastern and Southern | AFE | 2013 | 5.678921e+08 |
| 8 | Africa Eastern and Southern | AFE | 2012 | 5.525307e+08 |
| 9 | Africa Eastern and Southern | AFE | 2011 | 5.377930e+08 |
| 10 | Africa Eastern and Southern | AFE | 2010 | 5.234597e+08 |
| 11 | Africa Western and Central | AFW | 2020 | 4.661891e+08 |
| 12 | Africa Western and Central | AFW | 2019 | 4.543061e+08 |
| 13 | Africa Western and Central | AFW | 2018 | 4.426468e+08 |
| 14 | Africa Western and Central | AFW | 2017 | 4.311387e+08 |
| 15 | Africa Western and Central | AFW | 2016 | 4.197784e+08 |
| 16 | Africa Western and Central | AFW | 2015 | 4.086904e+08 |
| 17 | Africa Western and Central | AFW | 2014 | 3.978555e+08 |
| 18 | Africa Western and Central | AFW | 2013 | 3.872046e+08 |
| 19 | Africa Western and Central | AFW | 2012 | 3.767980e+08 |
| 20 | Africa Western and Central | AFW | 2011 | 3.664892e+08 |
| 21 | Africa Western and Central | AFW | 2010 | 3.563378e+08 |
| 22 | Arab World | ARB | 2020 | 4.492283e+08 |
| 23 | Arab World | ARB | 2019 | 4.414677e+08 |
| 24 | Arab World | ARB | 2018 | 4.325457e+08 |
| 25 | Arab World | ARB | 2017 | 4.236648e+08 |
| 26 | Arab World | ARB | 2016 | 4.150780e+08 |
| 27 | Arab World | ARB | 2015 | 4.065020e+08 |
| 28 | Arab World | ARB | 2014 | 3.979229e+08 |
| 29 | Arab World | ARB | 2013 | 3.891316e+08 |
| 30 | Arab World | ARB | 2012 | 3.803834e+08 |
| 31 | Arab World | ARB | 2011 | 3.723511e+08 |
| 32 | Arab World | ARB | 2010 | 3.644277e+08 |
| 33 | Caribbean small states | CSS | 2020 | 7.444768e+06 |
| 34 | Caribbean small states | CSS | 2019 | 7.424102e+06 |
| 35 | Caribbean small states | CSS | 2018 | 7.374650e+06 |
| 36 | Caribbean small states | CSS | 2017 | 7.303634e+06 |
| 37 | Caribbean small states | CSS | 2016 | 7.265272e+06 |
| 38 | Caribbean small states | CSS | 2015 | 7.224602e+06 |
| 39 | Caribbean small states | CSS | 2014 | 7.181044e+06 |
| 40 | Caribbean small states | CSS | 2013 | 7.135884e+06 |
| 41 | Caribbean small states | CSS | 2012 | 7.088996e+06 |
| 42 | Caribbean small states | CSS | 2011 | 7.044357e+06 |
| 43 | Caribbean small states | CSS | 2010 | 7.004428e+06 |
| 44 | Central Europe and the Baltics | CEB | 2020 | 1.021801e+08 |
| 45 | Central Europe and the Baltics | CEB | 2019 | 1.023985e+08 |
| 46 | Central Europe and the Baltics | CEB | 2018 | 1.025385e+08 |
| 47 | Central Europe and the Baltics | CEB | 2017 | 1.027401e+08 |
| 48 | Central Europe and the Baltics | CEB | 2016 | 1.029943e+08 |
| 49 | Central Europe and the Baltics | CEB | 2015 | 1.032579e+08 |
| 50 | Central Europe and the Baltics | CEB | 2014 | 1.034962e+08 |
| 51 | Central Europe and the Baltics | CEB | 2013 | 1.037137e+08 |
| 52 | Central Europe and the Baltics | CEB | 2012 | 1.039353e+08 |
| 53 | Central Europe and the Baltics | CEB | 2011 | 1.041740e+08 |
| 54 | Central Europe and the Baltics | CEB | 2010 | 1.044214e+08 |
| 55 | Early-demographic dividend | EAR | 2020 | 3.374384e+09 |
| 56 | Early-demographic dividend | EAR | 2019 | 3.334562e+09 |
| 57 | Early-demographic dividend | EAR | 2018 | 3.292897e+09 |
| 58 | Early-demographic dividend | EAR | 2017 | 3.250753e+09 |
| 59 | Early-demographic dividend | EAR | 2016 | 3.208370e+09 |
| 60 | Early-demographic dividend | EAR | 2015 | 3.165215e+09 |
| 61 | Early-demographic dividend | EAR | 2014 | 3.121656e+09 |
| 62 | Early-demographic dividend | EAR | 2013 | 3.078407e+09 |
| 63 | Early-demographic dividend | EAR | 2012 | 3.035160e+09 |
| 64 | Early-demographic dividend | EAR | 2011 | 2.991403e+09 |
| 65 | Early-demographic dividend | EAR | 2010 | 2.946286e+09 |
| 66 | East Asia & Pacific | EAS | 2020 | 2.363934e+09 |
| 67 | East Asia & Pacific | EAS | 2019 | 2.353857e+09 |
| 68 | East Asia & Pacific | EAS | 2018 | 2.341384e+09 |
| 69 | East Asia & Pacific | EAS | 2017 | 2.327133e+09 |
| 70 | East Asia & Pacific | EAS | 2016 | 2.310722e+09 |
| 71 | East Asia & Pacific | EAS | 2015 | 2.294507e+09 |
| 72 | East Asia & Pacific | EAS | 2014 | 2.278232e+09 |
| 73 | East Asia & Pacific | EAS | 2013 | 2.261274e+09 |
| 74 | East Asia & Pacific | EAS | 2012 | 2.243777e+09 |
| 75 | East Asia & Pacific | EAS | 2011 | 2.225992e+09 |
| 76 | East Asia & Pacific | EAS | 2010 | 2.210204e+09 |
| 77 | East Asia & Pacific (excluding high income) | EAP | 2020 | 2.116379e+09 |
| 78 | East Asia & Pacific (excluding high income) | EAP | 2019 | 2.106392e+09 |
| 79 | East Asia & Pacific (excluding high income) | EAP | 2018 | 2.094525e+09 |
| 80 | East Asia & Pacific (excluding high income) | EAP | 2017 | 2.080919e+09 |
| 81 | East Asia & Pacific (excluding high income) | EAP | 2016 | 2.065173e+09 |
| 82 | East Asia & Pacific (excluding high income) | EAP | 2015 | 2.049758e+09 |
| 83 | East Asia & Pacific (excluding high income) | EAP | 2014 | 2.034265e+09 |
| 84 | East Asia & Pacific (excluding high income) | EAP | 2013 | 2.018068e+09 |
| 85 | East Asia & Pacific (excluding high income) | EAP | 2012 | 2.001264e+09 |
| 86 | East Asia & Pacific (excluding high income) | EAP | 2011 | 1.984268e+09 |
| 87 | East Asia & Pacific (excluding high income) | EAP | 2010 | 1.969187e+09 |
| 88 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2020 | 2.090524e+09 |
| 89 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2019 | 2.080649e+09 |
| 90 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2018 | 2.068899e+09 |
| 91 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2017 | 2.055415e+09 |
| 92 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2016 | 2.039795e+09 |
| 93 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2015 | 2.024511e+09 |
| 94 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2014 | 2.009150e+09 |
| 95 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2013 | 1.993077e+09 |
| 96 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2012 | 1.976387e+09 |
| 97 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2011 | 1.959494e+09 |
| 98 | East Asia & Pacific (IDA & IBRD countries) | TEA | 2010 | 1.944511e+09 |
| 99 | Euro area | EMU | 2020 | 3.469611e+08 |
| 100 | Euro area | EMU | 2019 | 3.465180e+08 |
| 101 | Euro area | EMU | 2018 | 3.461530e+08 |
| 102 | Euro area | EMU | 2017 | 3.453706e+08 |
| 103 | Euro area | EMU | 2016 | 3.446838e+08 |
| 104 | Euro area | EMU | 2015 | 3.437183e+08 |
| 105 | Euro area | EMU | 2014 | 3.427253e+08 |
| 106 | Euro area | EMU | 2013 | 3.415845e+08 |
| 107 | Euro area | EMU | 2012 | 3.404507e+08 |
| 108 | Euro area | EMU | 2011 | 3.397230e+08 |
| 109 | Euro area | EMU | 2010 | 3.404670e+08 |
| 110 | Europe & Central Asia | ECS | 2020 | 9.223534e+08 |
| 111 | Europe & Central Asia | ECS | 2019 | 9.202775e+08 |
| 112 | Europe & Central Asia | ECS | 2018 | 9.173805e+08 |
| 113 | Europe & Central Asia | ECS | 2017 | 9.140783e+08 |
| 114 | Europe & Central Asia | ECS | 2016 | 9.106333e+08 |
| 115 | Europe & Central Asia | ECS | 2015 | 9.066954e+08 |
| 116 | Europe & Central Asia | ECS | 2014 | 9.026709e+08 |
| 117 | Europe & Central Asia | ECS | 2013 | 8.986074e+08 |
| 118 | Europe & Central Asia | ECS | 2012 | 8.946605e+08 |
| 119 | Europe & Central Asia | ECS | 2011 | 8.913294e+08 |
| 120 | Europe & Central Asia | ECS | 2010 | 8.891696e+08 |
| 121 | Europe & Central Asia (excluding high income) | ECA | 2020 | 4.000610e+08 |
| 122 | Europe & Central Asia (excluding high income) | ECA | 2019 | 3.986901e+08 |
| 123 | Europe & Central Asia (excluding high income) | ECA | 2018 | 3.966747e+08 |
| 124 | Europe & Central Asia (excluding high income) | ECA | 2017 | 3.947054e+08 |
| 125 | Europe & Central Asia (excluding high income) | ECA | 2016 | 3.925797e+08 |
| 126 | Europe & Central Asia (excluding high income) | ECA | 2015 | 3.902677e+08 |
| 127 | Europe & Central Asia (excluding high income) | ECA | 2014 | 3.879122e+08 |
| 128 | Europe & Central Asia (excluding high income) | ECA | 2013 | 3.856232e+08 |
| 129 | Europe & Central Asia (excluding high income) | ECA | 2012 | 3.833745e+08 |
| 130 | Europe & Central Asia (excluding high income) | ECA | 2011 | 3.813287e+08 |
| 131 | Europe & Central Asia (excluding high income) | ECA | 2010 | 3.790790e+08 |
| 132 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2020 | 4.612730e+08 |
| 133 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2019 | 4.600925e+08 |
| 134 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2018 | 4.582112e+08 |
| 135 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2017 | 4.563934e+08 |
| 136 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2016 | 4.544264e+08 |
| 137 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2015 | 4.522734e+08 |
| 138 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2014 | 4.500713e+08 |
| 139 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2013 | 4.479028e+08 |
| 140 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2012 | 4.457632e+08 |
| 141 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2011 | 4.438201e+08 |
| 142 | Europe & Central Asia (IDA & IBRD countries) | TEC | 2010 | 4.416641e+08 |
| 143 | European Union | EUU | 2020 | 4.476923e+08 |
| 144 | European Union | EUU | 2019 | 4.473672e+08 |
| 145 | European Union | EUU | 2018 | 4.470011e+08 |
| 146 | European Union | EUU | 2017 | 4.462152e+08 |
| 147 | European Union | EUU | 2016 | 4.455154e+08 |
| 148 | European Union | EUU | 2015 | 4.445701e+08 |
| 149 | European Union | EUU | 2014 | 4.436014e+08 |
| 150 | European Union | EUU | 2013 | 4.424962e+08 |
| 151 | European Union | EUU | 2012 | 4.414199e+08 |
| 152 | European Union | EUU | 2011 | 4.407697e+08 |
| 153 | European Union | EUU | 2010 | 4.415526e+08 |
| 154 | Fragile and conflict affected situations | FCS | 2020 | 9.797636e+08 |
| 155 | Fragile and conflict affected situations | FCS | 2019 | 9.577856e+08 |
| 156 | Fragile and conflict affected situations | FCS | 2018 | 9.367215e+08 |
| 157 | Fragile and conflict affected situations | FCS | 2017 | 9.164279e+08 |
| 158 | Fragile and conflict affected situations | FCS | 2016 | 8.962727e+08 |
| 159 | Fragile and conflict affected situations | FCS | 2015 | 8.764363e+08 |
| 160 | Fragile and conflict affected situations | FCS | 2014 | 8.570181e+08 |
| 161 | Fragile and conflict affected situations | FCS | 2013 | 8.374102e+08 |
| 162 | Fragile and conflict affected situations | FCS | 2012 | 8.174126e+08 |
| 163 | Fragile and conflict affected situations | FCS | 2011 | 7.977850e+08 |
| 164 | Fragile and conflict affected situations | FCS | 2010 | 7.787174e+08 |
| 165 | Heavily indebted poor countries (HIPC) | HPC | 2020 | 8.380666e+08 |
| 166 | Heavily indebted poor countries (HIPC) | HPC | 2019 | 8.151008e+08 |
| 167 | Heavily indebted poor countries (HIPC) | HPC | 2018 | 7.926159e+08 |
| 168 | Heavily indebted poor countries (HIPC) | HPC | 2017 | 7.703902e+08 |
| 169 | Heavily indebted poor countries (HIPC) | HPC | 2016 | 7.483566e+08 |
| 170 | Heavily indebted poor countries (HIPC) | HPC | 2015 | 7.271293e+08 |
| 171 | Heavily indebted poor countries (HIPC) | HPC | 2014 | 7.066172e+08 |
| 172 | Heavily indebted poor countries (HIPC) | HPC | 2013 | 6.866203e+08 |
| 173 | Heavily indebted poor countries (HIPC) | HPC | 2012 | 6.675209e+08 |
| 174 | Heavily indebted poor countries (HIPC) | HPC | 2011 | 6.489271e+08 |
| 175 | Heavily indebted poor countries (HIPC) | HPC | 2010 | 6.309532e+08 |
| 176 | High income | 2020 | 1.241719e+09 | |
| 177 | High income | 2019 | 1.236710e+09 | |
| 178 | High income | 2018 | 1.231509e+09 | |
| 179 | High income | 2017 | 1.225544e+09 | |
| 180 | High income | 2016 | 1.219355e+09 | |
| 181 | High income | 2015 | 1.212444e+09 | |
| 182 | High income | 2014 | 1.205686e+09 | |
| 183 | High income | 2013 | 1.198818e+09 | |
| 184 | High income | 2012 | 1.192042e+09 | |
| 185 | High income | 2011 | 1.185474e+09 | |
| 186 | High income | 2010 | 1.180459e+09 | |
| 187 | IBRD only | IBD | 2020 | 4.867092e+09 |
| 188 | IBRD only | IBD | 2019 | 4.832929e+09 |
| 189 | IBRD only | IBD | 2018 | 4.794556e+09 |
| 190 | IBRD only | IBD | 2017 | 4.753252e+09 |
| 191 | IBRD only | IBD | 2016 | 4.709004e+09 |
| 192 | IBRD only | IBD | 2015 | 4.663653e+09 |
| 193 | IBRD only | IBD | 2014 | 4.616585e+09 |
| 194 | IBRD only | IBD | 2013 | 4.567978e+09 |
| 195 | IBRD only | IBD | 2012 | 4.518974e+09 |
| 196 | IBRD only | IBD | 2011 | 4.471184e+09 |
| 197 | IBRD only | IBD | 2010 | 4.425785e+09 |
| 198 | IDA & IBRD total | IBT | 2020 | 6.627317e+09 |
| 199 | IDA & IBRD total | IBT | 2019 | 6.553978e+09 |
| 200 | IDA & IBRD total | IBT | 2018 | 6.477695e+09 |
| 201 | IDA & IBRD total | IBT | 2017 | 6.399653e+09 |
| 202 | IDA & IBRD total | IBT | 2016 | 6.319805e+09 |
| 203 | IDA & IBRD total | IBT | 2015 | 6.240231e+09 |
| 204 | IDA & IBRD total | IBT | 2014 | 6.160290e+09 |
| 205 | IDA & IBRD total | IBT | 2013 | 6.079502e+09 |
| 206 | IDA & IBRD total | IBT | 2012 | 5.998432e+09 |
| 207 | IDA & IBRD total | IBT | 2011 | 5.917716e+09 |
| 208 | IDA & IBRD total | IBT | 2010 | 5.838720e+09 |
| 209 | IDA blend | IDB | 2020 | 5.826371e+08 |
| 210 | IDA blend | IDB | 2019 | 5.706333e+08 |
| 211 | IDA blend | IDB | 2018 | 5.591556e+08 |
| 212 | IDA blend | IDB | 2017 | 5.479850e+08 |
| 213 | IDA blend | IDB | 2016 | 5.373584e+08 |
| 214 | IDA blend | IDB | 2015 | 5.271759e+08 |
| 215 | IDA blend | IDB | 2014 | 5.169001e+08 |
| 216 | IDA blend | IDB | 2013 | 5.064434e+08 |
| 217 | IDA blend | IDB | 2012 | 4.958685e+08 |
| 218 | IDA blend | IDB | 2011 | 4.849199e+08 |
| 219 | IDA blend | IDB | 2010 | 4.732045e+08 |
| 220 | IDA only | IDX | 2020 | 1.177589e+09 |
| 221 | IDA only | IDX | 2019 | 1.150416e+09 |
| 222 | IDA only | IDX | 2018 | 1.123984e+09 |
| 223 | IDA only | IDX | 2017 | 1.098416e+09 |
| 224 | IDA only | IDX | 2016 | 1.073443e+09 |
| 225 | IDA only | IDX | 2015 | 1.049402e+09 |
| 226 | IDA only | IDX | 2014 | 1.026805e+09 |
| 227 | IDA only | IDX | 2013 | 1.005081e+09 |
| 228 | IDA only | IDX | 2012 | 9.835899e+08 |
| 229 | IDA only | IDX | 2011 | 9.616121e+08 |
| 230 | IDA only | IDX | 2010 | 9.397310e+08 |
| 231 | IDA total | IDA | 2020 | 1.760226e+09 |
| 232 | IDA total | IDA | 2019 | 1.721049e+09 |
| 233 | IDA total | IDA | 2018 | 1.683140e+09 |
| 234 | IDA total | IDA | 2017 | 1.646401e+09 |
| 235 | IDA total | IDA | 2016 | 1.610801e+09 |
| 236 | IDA total | IDA | 2015 | 1.576578e+09 |
| 237 | IDA total | IDA | 2014 | 1.543705e+09 |
| 238 | IDA total | IDA | 2013 | 1.511524e+09 |
| 239 | IDA total | IDA | 2012 | 1.479458e+09 |
| 240 | IDA total | IDA | 2011 | 1.446532e+09 |
| 241 | IDA total | IDA | 2010 | 1.412935e+09 |
| 242 | Late-demographic dividend | LTE | 2020 | 2.317278e+09 |
| 243 | Late-demographic dividend | LTE | 2019 | 2.309492e+09 |
| 244 | Late-demographic dividend | LTE | 2018 | 2.298988e+09 |
| 245 | Late-demographic dividend | LTE | 2017 | 2.286628e+09 |
| 246 | Late-demographic dividend | LTE | 2016 | 2.272340e+09 |
| 247 | Late-demographic dividend | LTE | 2015 | 2.258406e+09 |
| 248 | Late-demographic dividend | LTE | 2014 | 2.244043e+09 |
| 249 | Late-demographic dividend | LTE | 2013 | 2.228485e+09 |
| 250 | Late-demographic dividend | LTE | 2012 | 2.212381e+09 |
| 251 | Late-demographic dividend | LTE | 2011 | 2.196512e+09 |
| 252 | Late-demographic dividend | LTE | 2010 | 2.182768e+09 |
| 253 | Latin America & Caribbean | LCN | 2020 | 6.505350e+08 |
| 254 | Latin America & Caribbean | LCN | 2019 | 6.452958e+08 |
| 255 | Latin America & Caribbean | LCN | 2018 | 6.396282e+08 |
| 256 | Latin America & Caribbean | LCN | 2017 | 6.337972e+08 |
| 257 | Latin America & Caribbean | LCN | 2016 | 6.276685e+08 |
| 258 | Latin America & Caribbean | LCN | 2015 | 6.213901e+08 |
| 259 | Latin America & Caribbean | LCN | 2014 | 6.150468e+08 |
| 260 | Latin America & Caribbean | LCN | 2013 | 6.086422e+08 |
| 261 | Latin America & Caribbean | LCN | 2012 | 6.021394e+08 |
| 262 | Latin America & Caribbean | LCN | 2011 | 5.955100e+08 |
| 263 | Latin America & Caribbean | LCN | 2010 | 5.888739e+08 |
| 264 | Latin America & Caribbean (excluding high income) | LAC | 2020 | 5.880112e+08 |
| 265 | Latin America & Caribbean (excluding high income) | LAC | 2019 | 5.827016e+08 |
| 266 | Latin America & Caribbean (excluding high income) | LAC | 2018 | 5.766205e+08 |
| 267 | Latin America & Caribbean (excluding high income) | LAC | 2017 | 5.703812e+08 |
| 268 | Latin America & Caribbean (excluding high income) | LAC | 2016 | 5.643779e+08 |
| 269 | Latin America & Caribbean (excluding high income) | LAC | 2015 | 5.585628e+08 |
| 270 | Latin America & Caribbean (excluding high income) | LAC | 2014 | 5.527818e+08 |
| 271 | Latin America & Caribbean (excluding high income) | LAC | 2013 | 5.469541e+08 |
| 272 | Latin America & Caribbean (excluding high income) | LAC | 2012 | 5.410483e+08 |
| 273 | Latin America & Caribbean (excluding high income) | LAC | 2011 | 5.350148e+08 |
| 274 | Latin America & Caribbean (excluding high income) | LAC | 2010 | 5.289783e+08 |
| 275 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2020 | 6.346804e+08 |
| 276 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2019 | 6.295156e+08 |
| 277 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2018 | 6.238413e+08 |
| 278 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2017 | 6.178758e+08 |
| 279 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2016 | 6.116681e+08 |
| 280 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2015 | 6.053356e+08 |
| 281 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2014 | 5.989494e+08 |
| 282 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2013 | 5.925076e+08 |
| 283 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2012 | 5.859869e+08 |
| 284 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2011 | 5.793347e+08 |
| 285 | Latin America & the Caribbean (IDA & IBRD coun... | TLA | 2010 | 5.726747e+08 |
| 286 | Least developed countries: UN classification | LDC | 2020 | 1.072971e+09 |
| 287 | Least developed countries: UN classification | LDC | 2019 | 1.047426e+09 |
| 288 | Least developed countries: UN classification | LDC | 2018 | 1.022732e+09 |
| 289 | Least developed countries: UN classification | LDC | 2017 | 9.985327e+08 |
| 290 | Least developed countries: UN classification | LDC | 2016 | 9.745162e+08 |
| 291 | Least developed countries: UN classification | LDC | 2015 | 9.511849e+08 |
| 292 | Least developed countries: UN classification | LDC | 2014 | 9.286617e+08 |
| 293 | Least developed countries: UN classification | LDC | 2013 | 9.064051e+08 |
| 294 | Least developed countries: UN classification | LDC | 2012 | 8.846540e+08 |
| 295 | Least developed countries: UN classification | LDC | 2011 | 8.634213e+08 |
| 296 | Least developed countries: UN classification | LDC | 2010 | 8.428072e+08 |
| 297 | Low & middle income | LMY | 2020 | 6.549996e+09 |
| 298 | Low & middle income | LMY | 2019 | 6.476093e+09 |
| 299 | Low & middle income | LMY | 2018 | 6.399037e+09 |
| 300 | Low & middle income | LMY | 2017 | 6.320334e+09 |
| 301 | Low & middle income | LMY | 2016 | 6.240319e+09 |
| 302 | Low & middle income | LMY | 2015 | 6.160876e+09 |
| 303 | Low & middle income | LMY | 2014 | 6.081161e+09 |
| 304 | Low & middle income | LMY | 2013 | 6.000647e+09 |
| 305 | Low & middle income | LMY | 2012 | 5.919874e+09 |
| 306 | Low & middle income | LMY | 2011 | 5.839474e+09 |
| 307 | Low & middle income | LMY | 2010 | 5.760811e+09 |
| 308 | Low income | 2020 | 6.670537e+08 | |
| 309 | Low income | 2019 | 6.487555e+08 | |
| 310 | Low income | 2018 | 6.308658e+08 | |
| 311 | Low income | 2017 | 6.139469e+08 | |
| 312 | Low income | 2016 | 5.976835e+08 | |
| 313 | Low income | 2015 | 5.821730e+08 | |
| 314 | Low income | 2014 | 5.677023e+08 | |
| 315 | Low income | 2013 | 5.538358e+08 | |
| 316 | Low income | 2012 | 5.400026e+08 | |
| 317 | Low income | 2011 | 5.255063e+08 | |
| 318 | Low income | 2010 | 5.108973e+08 | |
| 319 | Lower middle income | 2020 | 3.117226e+09 | |
| 320 | Lower middle income | 2019 | 3.075312e+09 | |
| 321 | Lower middle income | 2018 | 3.033153e+09 | |
| 322 | Lower middle income | 2017 | 2.990173e+09 | |
| 323 | Lower middle income | 2016 | 2.946639e+09 | |
| 324 | Lower middle income | 2015 | 2.902878e+09 | |
| 325 | Lower middle income | 2014 | 2.858673e+09 | |
| 326 | Lower middle income | 2013 | 2.813932e+09 | |
| 327 | Lower middle income | 2012 | 2.769675e+09 | |
| 328 | Lower middle income | 2011 | 2.726052e+09 | |
| 329 | Lower middle income | 2010 | 2.681991e+09 | |
| 330 | Middle East & North Africa | MEA | 2020 | 4.799666e+08 |
| 331 | Middle East & North Africa | MEA | 2019 | 4.732018e+08 |
| 332 | Middle East & North Africa | MEA | 2018 | 4.650735e+08 |
| 333 | Middle East & North Africa | MEA | 2017 | 4.568855e+08 |
| 334 | Middle East & North Africa | MEA | 2016 | 4.489174e+08 |
| 335 | Middle East & North Africa | MEA | 2015 | 4.405065e+08 |
| 336 | Middle East & North Africa | MEA | 2014 | 4.316646e+08 |
| 337 | Middle East & North Africa | MEA | 2013 | 4.227904e+08 |
| 338 | Middle East & North Africa | MEA | 2012 | 4.141176e+08 |
| 339 | Middle East & North Africa | MEA | 2011 | 4.060453e+08 |
| 340 | Middle East & North Africa | MEA | 2010 | 3.979976e+08 |
| 341 | Middle East & North Africa (excluding high inc... | MNA | 2020 | 4.118101e+08 |
| 342 | Middle East & North Africa (excluding high inc... | MNA | 2019 | 4.052594e+08 |
| 343 | Middle East & North Africa (excluding high inc... | MNA | 2018 | 3.983753e+08 |
| 344 | Middle East & North Africa (excluding high inc... | MNA | 2017 | 3.916074e+08 |
| 345 | Middle East & North Africa (excluding high inc... | MNA | 2016 | 3.850545e+08 |
| 346 | Middle East & North Africa (excluding high inc... | MNA | 2015 | 3.781373e+08 |
| 347 | Middle East & North Africa (excluding high inc... | MNA | 2014 | 3.707564e+08 |
| 348 | Middle East & North Africa (excluding high inc... | MNA | 2013 | 3.633102e+08 |
| 349 | Middle East & North Africa (excluding high inc... | MNA | 2012 | 3.562397e+08 |
| 350 | Middle East & North Africa (excluding high inc... | MNA | 2011 | 3.497702e+08 |
| 351 | Middle East & North Africa (excluding high inc... | MNA | 2010 | 3.433133e+08 |
| 352 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2020 | 4.070069e+08 |
| 353 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2019 | 4.005741e+08 |
| 354 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2018 | 3.938063e+08 |
| 355 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2017 | 3.871526e+08 |
| 356 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2016 | 3.806874e+08 |
| 357 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2015 | 3.738672e+08 |
| 358 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2014 | 3.665830e+08 |
| 359 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2013 | 3.592335e+08 |
| 360 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2012 | 3.522597e+08 |
| 361 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2011 | 3.458872e+08 |
| 362 | Middle East & North Africa (IDA & IBRD countries) | TMN | 2010 | 3.395272e+08 |
| 363 | Middle income | MIC | 2020 | 5.882943e+09 |
| 364 | Middle income | MIC | 2019 | 5.827338e+09 |
| 365 | Middle income | MIC | 2018 | 5.768171e+09 |
| 366 | Middle income | MIC | 2017 | 5.706387e+09 |
| 367 | Middle income | MIC | 2016 | 5.642636e+09 |
| 368 | Middle income | MIC | 2015 | 5.578703e+09 |
| 369 | Middle income | MIC | 2014 | 5.513458e+09 |
| 370 | Middle income | MIC | 2013 | 5.446811e+09 |
| 371 | Middle income | MIC | 2012 | 5.379871e+09 |
| 372 | Middle income | MIC | 2011 | 5.313968e+09 |
| 373 | Middle income | MIC | 2010 | 5.249914e+09 |
| 374 | North America | NAC | 2020 | 3.695826e+08 |
| 375 | North America | NAC | 2019 | 3.659951e+08 |
| 376 | North America | NAC | 2018 | 3.639672e+08 |
| 377 | North America | NAC | 2017 | 3.617312e+08 |
| 378 | North America | NAC | 2016 | 3.592458e+08 |
| 379 | North America | NAC | 2015 | 3.565071e+08 |
| 380 | North America | NAC | 2014 | 3.538889e+08 |
| 381 | North America | NAC | 2013 | 3.512079e+08 |
| 382 | North America | NAC | 2012 | 3.486567e+08 |
| 383 | North America | NAC | 2011 | 3.459874e+08 |
| 384 | North America | NAC | 2010 | 3.433972e+08 |
| 385 | Not classified | 2020 | NaN | |
| 386 | Not classified | 2019 | NaN | |
| 387 | Not classified | 2018 | NaN | |
| 388 | Not classified | 2017 | NaN | |
| 389 | Not classified | 2016 | NaN | |
| 390 | Not classified | 2015 | NaN | |
| 391 | Not classified | 2014 | NaN | |
| 392 | Not classified | 2013 | NaN | |
| 393 | Not classified | 2012 | NaN | |
| 394 | Not classified | 2011 | NaN | |
| 395 | Not classified | 2010 | NaN | |
| 396 | OECD members | OED | 2020 | 1.369465e+09 |
| 397 | OECD members | OED | 2019 | 1.362015e+09 |
| 398 | OECD members | OED | 2018 | 1.354836e+09 |
| 399 | OECD members | OED | 2017 | 1.346867e+09 |
| 400 | OECD members | OED | 2016 | 1.338791e+09 |
| 401 | OECD members | OED | 2015 | 1.330315e+09 |
| 402 | OECD members | OED | 2014 | 1.322076e+09 |
| 403 | OECD members | OED | 2013 | 1.313644e+09 |
| 404 | OECD members | OED | 2012 | 1.305513e+09 |
| 405 | OECD members | OED | 2011 | 1.297594e+09 |
| 406 | OECD members | OED | 2010 | 1.290948e+09 |
| 407 | Other small states | OSS | 2020 | 3.238146e+07 |
| 408 | Other small states | OSS | 2019 | 3.200548e+07 |
| 409 | Other small states | OSS | 2018 | 3.149449e+07 |
| 410 | Other small states | OSS | 2017 | 3.094031e+07 |
| 411 | Other small states | OSS | 2016 | 3.031000e+07 |
| 412 | Other small states | OSS | 2015 | 2.962104e+07 |
| 413 | Other small states | OSS | 2014 | 2.890755e+07 |
| 414 | Other small states | OSS | 2013 | 2.822579e+07 |
| 415 | Other small states | OSS | 2012 | 2.761727e+07 |
| 416 | Other small states | OSS | 2011 | 2.707292e+07 |
| 417 | Other small states | OSS | 2010 | 2.656599e+07 |
| 418 | Pacific island small states | PSS | 2020 | 2.566819e+06 |
| 419 | Pacific island small states | PSS | 2019 | 2.536070e+06 |
| 420 | Pacific island small states | PSS | 2018 | 2.510226e+06 |
| 421 | Pacific island small states | PSS | 2017 | 2.484263e+06 |
| 422 | Pacific island small states | PSS | 2016 | 2.457814e+06 |
| 423 | Pacific island small states | PSS | 2015 | 2.431426e+06 |
| 424 | Pacific island small states | PSS | 2014 | 2.405308e+06 |
| 425 | Pacific island small states | PSS | 2013 | 2.379069e+06 |
| 426 | Pacific island small states | PSS | 2012 | 2.353058e+06 |
| 427 | Pacific island small states | PSS | 2011 | 2.327284e+06 |
| 428 | Pacific island small states | PSS | 2010 | 2.301401e+06 |
| 429 | Post-demographic dividend | PST | 2020 | 1.117418e+09 |
| 430 | Post-demographic dividend | PST | 2019 | 1.113305e+09 |
| 431 | Post-demographic dividend | PST | 2018 | 1.110123e+09 |
| 432 | Post-demographic dividend | PST | 2017 | 1.106213e+09 |
| 433 | Post-demographic dividend | PST | 2016 | 1.102020e+09 |
| 434 | Post-demographic dividend | PST | 2015 | 1.097061e+09 |
| 435 | Post-demographic dividend | PST | 2014 | 1.092180e+09 |
| 436 | Post-demographic dividend | PST | 2013 | 1.087231e+09 |
| 437 | Post-demographic dividend | PST | 2012 | 1.082489e+09 |
| 438 | Post-demographic dividend | PST | 2011 | 1.077987e+09 |
| 439 | Post-demographic dividend | PST | 2010 | 1.075046e+09 |
| 440 | Pre-demographic dividend | PRE | 2020 | 9.842134e+08 |
| 441 | Pre-demographic dividend | PRE | 2019 | 9.575032e+08 |
| 442 | Pre-demographic dividend | PRE | 2018 | 9.314672e+08 |
| 443 | Pre-demographic dividend | PRE | 2017 | 9.059879e+08 |
| 444 | Pre-demographic dividend | PRE | 2016 | 8.808915e+08 |
| 445 | Pre-demographic dividend | PRE | 2015 | 8.564203e+08 |
| 446 | Pre-demographic dividend | PRE | 2014 | 8.324698e+08 |
| 447 | Pre-demographic dividend | PRE | 2013 | 8.085421e+08 |
| 448 | Pre-demographic dividend | PRE | 2012 | 7.848228e+08 |
| 449 | Pre-demographic dividend | PRE | 2011 | 7.617171e+08 |
| 450 | Pre-demographic dividend | PRE | 2010 | 7.395260e+08 |
| 451 | Small states | SST | 2020 | 4.239305e+07 |
| 452 | Small states | SST | 2019 | 4.196565e+07 |
| 453 | Small states | SST | 2018 | 4.137937e+07 |
| 454 | Small states | SST | 2017 | 4.072821e+07 |
| 455 | Small states | SST | 2016 | 4.003308e+07 |
| 456 | Small states | SST | 2015 | 3.927707e+07 |
| 457 | Small states | SST | 2014 | 3.849390e+07 |
| 458 | Small states | SST | 2013 | 3.774074e+07 |
| 459 | Small states | SST | 2012 | 3.705933e+07 |
| 460 | Small states | SST | 2011 | 3.644456e+07 |
| 461 | Small states | SST | 2010 | 3.587182e+07 |
| 462 | South Asia | SAS | 2020 | 1.882532e+09 |
| 463 | South Asia | SAS | 2019 | 1.861599e+09 |
| 464 | South Asia | SAS | 2018 | 1.840534e+09 |
| 465 | South Asia | SAS | 2017 | 1.818932e+09 |
| 466 | South Asia | SAS | 2016 | 1.797073e+09 |
| 467 | South Asia | SAS | 2015 | 1.775545e+09 |
| 468 | South Asia | SAS | 2014 | 1.754030e+09 |
| 469 | South Asia | SAS | 2013 | 1.731684e+09 |
| 470 | South Asia | SAS | 2012 | 1.708707e+09 |
| 471 | South Asia | SAS | 2011 | 1.684898e+09 |
| 472 | South Asia | SAS | 2010 | 1.660546e+09 |
| 473 | South Asia (IDA & IBRD) | TSA | 2020 | 1.882532e+09 |
| 474 | South Asia (IDA & IBRD) | TSA | 2019 | 1.861599e+09 |
| 475 | South Asia (IDA & IBRD) | TSA | 2018 | 1.840534e+09 |
| 476 | South Asia (IDA & IBRD) | TSA | 2017 | 1.818932e+09 |
| 477 | South Asia (IDA & IBRD) | TSA | 2016 | 1.797073e+09 |
| 478 | South Asia (IDA & IBRD) | TSA | 2015 | 1.775545e+09 |
| 479 | South Asia (IDA & IBRD) | TSA | 2014 | 1.754030e+09 |
| 480 | South Asia (IDA & IBRD) | TSA | 2013 | 1.731684e+09 |
| 481 | South Asia (IDA & IBRD) | TSA | 2012 | 1.708707e+09 |
| 482 | South Asia (IDA & IBRD) | TSA | 2011 | 1.684898e+09 |
| 483 | South Asia (IDA & IBRD) | TSA | 2010 | 1.660546e+09 |
| 484 | Sub-Saharan Africa | SSF | 2020 | 1.151302e+09 |
| 485 | Sub-Saharan Africa | SSF | 2019 | 1.121549e+09 |
| 486 | Sub-Saharan Africa | SSF | 2018 | 1.092404e+09 |
| 487 | Sub-Saharan Africa | SSF | 2017 | 1.063885e+09 |
| 488 | Sub-Saharan Africa | SSF | 2016 | 1.036156e+09 |
| 489 | Sub-Saharan Africa | SSF | 2015 | 1.008699e+09 |
| 490 | Sub-Saharan Africa | SSF | 2014 | 9.815066e+08 |
| 491 | Sub-Saharan Africa | SSF | 2013 | 9.550967e+08 |
| 492 | Sub-Saharan Africa | SSF | 2012 | 9.293287e+08 |
| 493 | Sub-Saharan Africa | SSF | 2011 | 9.042822e+08 |
| 494 | Sub-Saharan Africa | SSF | 2010 | 8.797974e+08 |
| 495 | Sub-Saharan Africa (excluding high income) | SSA | 2020 | 1.151204e+09 |
| 496 | Sub-Saharan Africa (excluding high income) | SSA | 2019 | 1.121451e+09 |
| 497 | Sub-Saharan Africa (excluding high income) | SSA | 2018 | 1.092307e+09 |
| 498 | Sub-Saharan Africa (excluding high income) | SSA | 2017 | 1.063789e+09 |
| 499 | Sub-Saharan Africa (excluding high income) | SSA | 2016 | 1.036061e+09 |
| 500 | Sub-Saharan Africa (excluding high income) | SSA | 2015 | 1.008605e+09 |
| 501 | Sub-Saharan Africa (excluding high income) | SSA | 2014 | 9.814152e+08 |
| 502 | Sub-Saharan Africa (excluding high income) | SSA | 2013 | 9.550068e+08 |
| 503 | Sub-Saharan Africa (excluding high income) | SSA | 2012 | 9.292404e+08 |
| 504 | Sub-Saharan Africa (excluding high income) | SSA | 2011 | 9.041947e+08 |
| 505 | Sub-Saharan Africa (excluding high income) | SSA | 2010 | 8.797076e+08 |
| 506 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2020 | 1.151302e+09 |
| 507 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2019 | 1.121549e+09 |
| 508 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2018 | 1.092404e+09 |
| 509 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2017 | 1.063885e+09 |
| 510 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2016 | 1.036156e+09 |
| 511 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2015 | 1.008699e+09 |
| 512 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2014 | 9.815066e+08 |
| 513 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2013 | 9.550967e+08 |
| 514 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2012 | 9.293287e+08 |
| 515 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2011 | 9.042822e+08 |
| 516 | Sub-Saharan Africa (IDA & IBRD countries) | TSS | 2010 | 8.797974e+08 |
| 517 | Upper middle income | 2020 | 2.765717e+09 | |
| 518 | Upper middle income | 2019 | 2.752026e+09 | |
| 519 | Upper middle income | 2018 | 2.735018e+09 | |
| 520 | Upper middle income | 2017 | 2.716215e+09 | |
| 521 | Upper middle income | 2016 | 2.695996e+09 | |
| 522 | Upper middle income | 2015 | 2.675825e+09 | |
| 523 | Upper middle income | 2014 | 2.654785e+09 | |
| 524 | Upper middle income | 2013 | 2.632879e+09 | |
| 525 | Upper middle income | 2012 | 2.610196e+09 | |
| 526 | Upper middle income | 2011 | 2.587915e+09 | |
| 527 | Upper middle income | 2010 | 2.567923e+09 | |
| 528 | World | WLD | 2020 | 7.820206e+09 |
| 529 | World | WLD | 2019 | 7.741775e+09 |
| 530 | World | WLD | 2018 | 7.660371e+09 |
| 531 | World | WLD | 2017 | 7.576442e+09 |
| 532 | World | WLD | 2016 | 7.490415e+09 |
| 533 | World | WLD | 2015 | 7.403850e+09 |
| 534 | World | WLD | 2014 | 7.317040e+09 |
| 535 | World | WLD | 2013 | 7.229303e+09 |
| 536 | World | WLD | 2012 | 7.141386e+09 |
| 537 | World | WLD | 2011 | 7.054044e+09 |
| 538 | World | WLD | 2010 | 6.969986e+09 |
| 539 | Afghanistan | AFG | 2020 | 3.897223e+07 |
| 540 | Afghanistan | AFG | 2019 | 3.776950e+07 |
| 541 | Afghanistan | AFG | 2018 | 3.668678e+07 |
| 542 | Afghanistan | AFG | 2017 | 3.564342e+07 |
| 543 | Afghanistan | AFG | 2016 | 3.463621e+07 |
| 544 | Afghanistan | AFG | 2015 | 3.375350e+07 |
| 545 | Afghanistan | AFG | 2014 | 3.271621e+07 |
| 546 | Afghanistan | AFG | 2013 | 3.154121e+07 |
| 547 | Afghanistan | AFG | 2012 | 3.046648e+07 |
| 548 | Afghanistan | AFG | 2011 | 2.924916e+07 |
| 549 | Afghanistan | AFG | 2010 | 2.818967e+07 |
| 550 | Albania | ALB | 2020 | 2.837849e+06 |
| 551 | Albania | ALB | 2019 | 2.854191e+06 |
| 552 | Albania | ALB | 2018 | 2.866376e+06 |
| 553 | Albania | ALB | 2017 | 2.873457e+06 |
| 554 | Albania | ALB | 2016 | 2.876101e+06 |
| 555 | Albania | ALB | 2015 | 2.880703e+06 |
| 556 | Albania | ALB | 2014 | 2.889104e+06 |
| 557 | Albania | ALB | 2013 | 2.895092e+06 |
| 558 | Albania | ALB | 2012 | 2.900401e+06 |
| 559 | Albania | ALB | 2011 | 2.905195e+06 |
| 560 | Albania | ALB | 2010 | 2.913021e+06 |
| 561 | Algeria | DZA | 2020 | 4.345167e+07 |
| 562 | Algeria | DZA | 2019 | 4.270537e+07 |
| 563 | Algeria | DZA | 2018 | 4.192701e+07 |
| 564 | Algeria | DZA | 2017 | 4.113655e+07 |
| 565 | Algeria | DZA | 2016 | 4.033933e+07 |
| 566 | Algeria | DZA | 2015 | 3.954315e+07 |
| 567 | Algeria | DZA | 2014 | 3.876017e+07 |
| 568 | Algeria | DZA | 2013 | 3.800063e+07 |
| 569 | Algeria | DZA | 2012 | 3.726056e+07 |
| 570 | Algeria | DZA | 2011 | 3.654354e+07 |
| 571 | Algeria | DZA | 2010 | 3.585634e+07 |
| 572 | American Samoa | ASM | 2020 | 4.618900e+04 |
| 573 | American Samoa | ASM | 2019 | 4.732100e+04 |
| 574 | American Samoa | ASM | 2018 | 4.842400e+04 |
| 575 | American Samoa | ASM | 2017 | 4.946300e+04 |
| 576 | American Samoa | ASM | 2016 | 5.044800e+04 |
| 577 | American Samoa | ASM | 2015 | 5.136800e+04 |
| 578 | American Samoa | ASM | 2014 | 5.221700e+04 |
| 579 | American Samoa | ASM | 2013 | 5.299500e+04 |
| 580 | American Samoa | ASM | 2012 | 5.369100e+04 |
| 581 | American Samoa | ASM | 2011 | 5.431000e+04 |
| 582 | American Samoa | ASM | 2010 | 5.484900e+04 |
| 583 | Andorra | AND | 2020 | 7.770000e+04 |
| 584 | Andorra | AND | 2019 | 7.634300e+04 |
| 585 | Andorra | AND | 2018 | 7.501300e+04 |
| 586 | Andorra | AND | 2017 | 7.383700e+04 |
| 587 | Andorra | AND | 2016 | 7.254000e+04 |
| 588 | Andorra | AND | 2015 | 7.174600e+04 |
| 589 | Andorra | AND | 2014 | 7.162100e+04 |
| 590 | Andorra | AND | 2013 | 7.136700e+04 |
| 591 | Andorra | AND | 2012 | 7.101300e+04 |
| 592 | Andorra | AND | 2011 | 7.056700e+04 |
| 593 | Andorra | AND | 2010 | 7.151900e+04 |
| 594 | Angola | AGO | 2020 | 3.342849e+07 |
| 595 | Angola | AGO | 2019 | 3.235359e+07 |
| 596 | Angola | AGO | 2018 | 3.127353e+07 |
| 597 | Angola | AGO | 2017 | 3.020863e+07 |
| 598 | Angola | AGO | 2016 | 2.915475e+07 |
| 599 | Angola | AGO | 2015 | 2.812772e+07 |
| 600 | Angola | AGO | 2014 | 2.712834e+07 |
| 601 | Angola | AGO | 2013 | 2.614700e+07 |
| 602 | Angola | AGO | 2012 | 2.518829e+07 |
| 603 | Angola | AGO | 2011 | 2.425911e+07 |
| 604 | Angola | AGO | 2010 | 2.336418e+07 |
| 605 | Antigua and Barbuda | ATG | 2020 | 9.266400e+04 |
| 606 | Antigua and Barbuda | ATG | 2019 | 9.211700e+04 |
| 607 | Antigua and Barbuda | ATG | 2018 | 9.162600e+04 |
| 608 | Antigua and Barbuda | ATG | 2017 | 9.111900e+04 |
| 609 | Antigua and Barbuda | ATG | 2016 | 9.056400e+04 |
| 610 | Antigua and Barbuda | ATG | 2015 | 8.994100e+04 |
| 611 | Antigua and Barbuda | ATG | 2014 | 8.923600e+04 |
| 612 | Antigua and Barbuda | ATG | 2013 | 8.849700e+04 |
| 613 | Antigua and Barbuda | ATG | 2012 | 8.767400e+04 |
| 614 | Antigua and Barbuda | ATG | 2011 | 8.672900e+04 |
| 615 | Antigua and Barbuda | ATG | 2010 | 8.569500e+04 |
| 616 | Argentina | ARG | 2020 | 4.537676e+07 |
| 617 | Argentina | ARG | 2019 | 4.493871e+07 |
| 618 | Argentina | ARG | 2018 | 4.449450e+07 |
| 619 | Argentina | ARG | 2017 | 4.404481e+07 |
| 620 | Argentina | ARG | 2016 | 4.359037e+07 |
| 621 | Argentina | ARG | 2015 | 4.313197e+07 |
| 622 | Argentina | ARG | 2014 | 4.266950e+07 |
| 623 | Argentina | ARG | 2013 | 4.220294e+07 |
| 624 | Argentina | ARG | 2012 | 4.173327e+07 |
| 625 | Argentina | ARG | 2011 | 4.126149e+07 |
| 626 | Argentina | ARG | 2010 | 4.078845e+07 |
| 627 | Armenia | ARM | 2020 | 2.805608e+06 |
| 628 | Armenia | ARM | 2019 | 2.820602e+06 |
| 629 | Armenia | ARM | 2018 | 2.836557e+06 |
| 630 | Armenia | ARM | 2017 | 2.851923e+06 |
| 631 | Armenia | ARM | 2016 | 2.865835e+06 |
| 632 | Armenia | ARM | 2015 | 2.878595e+06 |
| 633 | Armenia | ARM | 2014 | 2.889930e+06 |
| 634 | Armenia | ARM | 2013 | 2.901385e+06 |
| 635 | Armenia | ARM | 2012 | 2.914421e+06 |
| 636 | Armenia | ARM | 2011 | 2.928976e+06 |
| 637 | Armenia | ARM | 2010 | 2.946293e+06 |
| 638 | Aruba | ABW | 2020 | 1.065850e+05 |
| 639 | Aruba | ABW | 2019 | 1.064420e+05 |
| 640 | Aruba | ABW | 2018 | 1.059620e+05 |
| 641 | Aruba | ABW | 2017 | 1.054390e+05 |
| 642 | Aruba | ABW | 2016 | 1.048740e+05 |
| 643 | Aruba | ABW | 2015 | 1.042570e+05 |
| 644 | Aruba | ABW | 2014 | 1.035940e+05 |
| 645 | Aruba | ABW | 2013 | 1.028800e+05 |
| 646 | Aruba | ABW | 2012 | 1.021120e+05 |
| 647 | Aruba | ABW | 2011 | 1.012880e+05 |
| 648 | Aruba | ABW | 2010 | 1.003410e+05 |
| 649 | Australia | AUS | 2020 | 2.564925e+07 |
| 650 | Australia | AUS | 2019 | 2.533483e+07 |
| 651 | Australia | AUS | 2018 | 2.496326e+07 |
| 652 | Australia | AUS | 2017 | 2.459259e+07 |
| 653 | Australia | AUS | 2016 | 2.419091e+07 |
| 654 | Australia | AUS | 2015 | 2.381600e+07 |
| 655 | Australia | AUS | 2014 | 2.347569e+07 |
| 656 | Australia | AUS | 2013 | 2.312813e+07 |
| 657 | Australia | AUS | 2012 | 2.273346e+07 |
| 658 | Australia | AUS | 2011 | 2.234002e+07 |
| 659 | Australia | AUS | 2010 | 2.203175e+07 |
| 660 | Austria | AUT | 2020 | 8.916864e+06 |
| 661 | Austria | AUT | 2019 | 8.879920e+06 |
| 662 | Austria | AUT | 2018 | 8.840521e+06 |
| 663 | Austria | AUT | 2017 | 8.797566e+06 |
| 664 | Austria | AUT | 2016 | 8.736668e+06 |
| 665 | Austria | AUT | 2015 | 8.642699e+06 |
| 666 | Austria | AUT | 2014 | 8.546356e+06 |
| 667 | Austria | AUT | 2013 | 8.479823e+06 |
| 668 | Austria | AUT | 2012 | 8.429991e+06 |
| 669 | Austria | AUT | 2011 | 8.391643e+06 |
| 670 | Austria | AUT | 2010 | 8.363404e+06 |
| 671 | Azerbaijan | AZE | 2020 | 1.009312e+07 |
| 672 | Azerbaijan | AZE | 2019 | 1.002428e+07 |
| 673 | Azerbaijan | AZE | 2018 | 9.939771e+06 |
| 674 | Azerbaijan | AZE | 2017 | 9.854033e+06 |
| 675 | Azerbaijan | AZE | 2016 | 9.757812e+06 |
| 676 | Azerbaijan | AZE | 2015 | 9.649341e+06 |
| 677 | Azerbaijan | AZE | 2014 | 9.535079e+06 |
| 678 | Azerbaijan | AZE | 2013 | 9.416801e+06 |
| 679 | Azerbaijan | AZE | 2012 | 9.295784e+06 |
| 680 | Azerbaijan | AZE | 2011 | 9.173082e+06 |
| 681 | Azerbaijan | AZE | 2010 | 9.054332e+06 |
| 682 | Bahamas, The | BHS | 2020 | 4.064710e+05 |
| 683 | Bahamas, The | BHS | 2019 | 4.045570e+05 |
| 684 | Bahamas, The | BHS | 2018 | 4.019060e+05 |
| 685 | Bahamas, The | BHS | 2017 | 3.990200e+05 |
| 686 | Bahamas, The | BHS | 2016 | 3.959760e+05 |
| 687 | Bahamas, The | BHS | 2015 | 3.926970e+05 |
| 688 | Bahamas, The | BHS | 2014 | 3.891310e+05 |
| 689 | Bahamas, The | BHS | 2013 | 3.856500e+05 |
| 690 | Bahamas, The | BHS | 2012 | 3.820610e+05 |
| 691 | Bahamas, The | BHS | 2011 | 3.779500e+05 |
| 692 | Bahamas, The | BHS | 2010 | 3.732720e+05 |
| 693 | Bahrain | BHR | 2020 | 1.477469e+06 |
| 694 | Bahrain | BHR | 2019 | 1.494188e+06 |
| 695 | Bahrain | BHR | 2018 | 1.487340e+06 |
| 696 | Bahrain | BHR | 2017 | 1.456834e+06 |
| 697 | Bahrain | BHR | 2016 | 1.409661e+06 |
| 698 | Bahrain | BHR | 2015 | 1.362142e+06 |
| 699 | Bahrain | BHR | 2014 | 1.311134e+06 |
| 700 | Bahrain | BHR | 2013 | 1.261673e+06 |
| 701 | Bahrain | BHR | 2012 | 1.224939e+06 |
| 702 | Bahrain | BHR | 2011 | 1.212077e+06 |
| 703 | Bahrain | BHR | 2010 | 1.213645e+06 |
| 704 | Bangladesh | BGD | 2020 | 1.674210e+08 |
| 705 | Bangladesh | BGD | 2019 | 1.655162e+08 |
| 706 | Bangladesh | BGD | 2018 | 1.636840e+08 |
| 707 | Bangladesh | BGD | 2017 | 1.617940e+08 |
| 708 | Bangladesh | BGD | 2016 | 1.597846e+08 |
| 709 | Bangladesh | BGD | 2015 | 1.578300e+08 |
| 710 | Bangladesh | BGD | 2014 | 1.559613e+08 |
| 711 | Bangladesh | BGD | 2013 | 1.540301e+08 |
| 712 | Bangladesh | BGD | 2012 | 1.520906e+08 |
| 713 | Bangladesh | BGD | 2011 | 1.502110e+08 |
| 714 | Bangladesh | BGD | 2010 | 1.483911e+08 |
| 715 | Barbados | BRB | 2020 | 2.806930e+05 |
| 716 | Barbados | BRB | 2019 | 2.801800e+05 |
| 717 | Barbados | BRB | 2018 | 2.796880e+05 |
| 718 | Barbados | BRB | 2017 | 2.791870e+05 |
| 719 | Barbados | BRB | 2016 | 2.786490e+05 |
| 720 | Barbados | BRB | 2015 | 2.780830e+05 |
| 721 | Barbados | BRB | 2014 | 2.774930e+05 |
| 722 | Barbados | BRB | 2013 | 2.768650e+05 |
| 723 | Barbados | BRB | 2012 | 2.761970e+05 |
| 724 | Barbados | BRB | 2011 | 2.754860e+05 |
| 725 | Barbados | BRB | 2010 | 2.747110e+05 |
| 726 | Belarus | BLR | 2020 | 9.379952e+06 |
| 727 | Belarus | BLR | 2019 | 9.419758e+06 |
| 728 | Belarus | BLR | 2018 | 9.438785e+06 |
| 729 | Belarus | BLR | 2017 | 9.458989e+06 |
| 730 | Belarus | BLR | 2016 | 9.469379e+06 |
| 731 | Belarus | BLR | 2015 | 9.461076e+06 |
| 732 | Belarus | BLR | 2014 | 9.448515e+06 |
| 733 | Belarus | BLR | 2013 | 9.443211e+06 |
| 734 | Belarus | BLR | 2012 | 9.446836e+06 |
| 735 | Belarus | BLR | 2011 | 9.461643e+06 |
| 736 | Belarus | BLR | 2010 | 9.483836e+06 |
| 737 | Belgium | BEL | 2020 | 1.153860e+07 |
| 738 | Belgium | BEL | 2019 | 1.148898e+07 |
| 739 | Belgium | BEL | 2018 | 1.142705e+07 |
| 740 | Belgium | BEL | 2017 | 1.137516e+07 |
| 741 | Belgium | BEL | 2016 | 1.133142e+07 |
| 742 | Belgium | BEL | 2015 | 1.127420e+07 |
| 743 | Belgium | BEL | 2014 | 1.120906e+07 |
| 744 | Belgium | BEL | 2013 | 1.115941e+07 |
| 745 | Belgium | BEL | 2012 | 1.110693e+07 |
| 746 | Belgium | BEL | 2011 | 1.103826e+07 |
| 747 | Belgium | BEL | 2010 | 1.089559e+07 |
| 748 | Belize | BLZ | 2020 | 3.949210e+05 |
| 749 | Belize | BLZ | 2019 | 3.890950e+05 |
| 750 | Belize | BLZ | 2018 | 3.820660e+05 |
| 751 | Belize | BLZ | 2017 | 3.746930e+05 |
| 752 | Belize | BLZ | 2016 | 3.673130e+05 |
| 753 | Belize | BLZ | 2015 | 3.598710e+05 |
| 754 | Belize | BLZ | 2014 | 3.523350e+05 |
| 755 | Belize | BLZ | 2013 | 3.446880e+05 |
| 756 | Belize | BLZ | 2012 | 3.370590e+05 |
| 757 | Belize | BLZ | 2011 | 3.295380e+05 |
| 758 | Belize | BLZ | 2010 | 3.221060e+05 |
| 759 | Benin | BEN | 2020 | 1.264312e+07 |
| 760 | Benin | BEN | 2019 | 1.229044e+07 |
| 761 | Benin | BEN | 2018 | 1.194068e+07 |
| 762 | Benin | BEN | 2017 | 1.159678e+07 |
| 763 | Benin | BEN | 2016 | 1.126008e+07 |
| 764 | Benin | BEN | 2015 | 1.093278e+07 |
| 765 | Benin | BEN | 2014 | 1.061484e+07 |
| 766 | Benin | BEN | 2013 | 1.030873e+07 |
| 767 | Benin | BEN | 2012 | 1.001408e+07 |
| 768 | Benin | BEN | 2011 | 9.726380e+06 |
| 769 | Benin | BEN | 2010 | 9.445710e+06 |
| 770 | Bermuda | BMU | 2020 | 6.389300e+04 |
| 771 | Bermuda | BMU | 2019 | 6.391100e+04 |
| 772 | Bermuda | BMU | 2018 | 6.391800e+04 |
| 773 | Bermuda | BMU | 2017 | 6.387300e+04 |
| 774 | Bermuda | BMU | 2016 | 6.455400e+04 |
| 775 | Bermuda | BMU | 2015 | 6.523700e+04 |
| 776 | Bermuda | BMU | 2014 | 6.513800e+04 |
| 777 | Bermuda | BMU | 2013 | 6.500100e+04 |
| 778 | Bermuda | BMU | 2012 | 6.479800e+04 |
| 779 | Bermuda | BMU | 2011 | 6.456400e+04 |
| 780 | Bermuda | BMU | 2010 | 6.512400e+04 |
| 781 | Bhutan | BTN | 2020 | 7.725060e+05 |
| 782 | Bhutan | BTN | 2019 | 7.674590e+05 |
| 783 | Bhutan | BTN | 2018 | 7.620960e+05 |
| 784 | Bhutan | BTN | 2017 | 7.561210e+05 |
| 785 | Bhutan | BTN | 2016 | 7.497610e+05 |
| 786 | Bhutan | BTN | 2015 | 7.432740e+05 |
| 787 | Bhutan | BTN | 2014 | 7.363570e+05 |
| 788 | Bhutan | BTN | 2013 | 7.288890e+05 |
| 789 | Bhutan | BTN | 2012 | 7.211450e+05 |
| 790 | Bhutan | BTN | 2011 | 7.133310e+05 |
| 791 | Bhutan | BTN | 2010 | 7.055160e+05 |
| 792 | Bolivia | BOL | 2020 | 1.193616e+07 |
| 793 | Bolivia | BOL | 2019 | 1.177732e+07 |
| 794 | Bolivia | BOL | 2018 | 1.160690e+07 |
| 795 | Bolivia | BOL | 2017 | 1.143553e+07 |
| 796 | Bolivia | BOL | 2016 | 1.126302e+07 |
| 797 | Bolivia | BOL | 2015 | 1.109008e+07 |
| 798 | Bolivia | BOL | 2014 | 1.091699e+07 |
| 799 | Bolivia | BOL | 2013 | 1.074335e+07 |
| 800 | Bolivia | BOL | 2012 | 1.056970e+07 |
| 801 | Bolivia | BOL | 2011 | 1.039625e+07 |
| 802 | Bolivia | BOL | 2010 | 1.022327e+07 |
| 803 | Bosnia and Herzegovina | BIH | 2020 | 3.318407e+06 |
| 804 | Bosnia and Herzegovina | BIH | 2019 | 3.360711e+06 |
| 805 | Bosnia and Herzegovina | BIH | 2018 | 3.400129e+06 |
| 806 | Bosnia and Herzegovina | BIH | 2017 | 3.440027e+06 |
| 807 | Bosnia and Herzegovina | BIH | 2016 | 3.480986e+06 |
| 808 | Bosnia and Herzegovina | BIH | 2015 | 3.524324e+06 |
| 809 | Bosnia and Herzegovina | BIH | 2014 | 3.571068e+06 |
| 810 | Bosnia and Herzegovina | BIH | 2013 | 3.617559e+06 |
| 811 | Bosnia and Herzegovina | BIH | 2012 | 3.674374e+06 |
| 812 | Bosnia and Herzegovina | BIH | 2011 | 3.743142e+06 |
| 813 | Bosnia and Herzegovina | BIH | 2010 | 3.811088e+06 |
| 814 | Botswana | BWA | 2020 | 2.546402e+06 |
| 815 | Botswana | BWA | 2019 | 2.499702e+06 |
| 816 | Botswana | BWA | 2018 | 2.451409e+06 |
| 817 | Botswana | BWA | 2017 | 2.401840e+06 |
| 818 | Botswana | BWA | 2016 | 2.352416e+06 |
| 819 | Botswana | BWA | 2015 | 2.305171e+06 |
| 820 | Botswana | BWA | 2014 | 2.260376e+06 |
| 821 | Botswana | BWA | 2013 | 2.217278e+06 |
| 822 | Botswana | BWA | 2012 | 2.175425e+06 |
| 823 | Botswana | BWA | 2011 | 2.134037e+06 |
| 824 | Botswana | BWA | 2010 | 2.091664e+06 |
| 825 | Brazil | BRA | 2020 | 2.131963e+08 |
| 826 | Brazil | BRA | 2019 | 2.117829e+08 |
| 827 | Brazil | BRA | 2018 | 2.101666e+08 |
| 828 | Brazil | BRA | 2017 | 2.085050e+08 |
| 829 | Brazil | BRA | 2016 | 2.068596e+08 |
| 830 | Brazil | BRA | 2015 | 2.051882e+08 |
| 831 | Brazil | BRA | 2014 | 2.034596e+08 |
| 832 | Brazil | BRA | 2013 | 2.017218e+08 |
| 833 | Brazil | BRA | 2012 | 1.999777e+08 |
| 834 | Brazil | BRA | 2011 | 1.981853e+08 |
| 835 | Brazil | BRA | 2010 | 1.963535e+08 |
| 836 | British Virgin Islands | VGB | 2020 | 3.091000e+04 |
| 837 | British Virgin Islands | VGB | 2019 | 3.061000e+04 |
| 838 | British Virgin Islands | VGB | 2018 | 3.033500e+04 |
| 839 | British Virgin Islands | VGB | 2017 | 3.006000e+04 |
| 840 | British Virgin Islands | VGB | 2016 | 2.973900e+04 |
| 841 | British Virgin Islands | VGB | 2015 | 2.936600e+04 |
| 842 | British Virgin Islands | VGB | 2014 | 2.897100e+04 |
| 843 | British Virgin Islands | VGB | 2013 | 2.865700e+04 |
| 844 | British Virgin Islands | VGB | 2012 | 2.842100e+04 |
| 845 | British Virgin Islands | VGB | 2011 | 2.796200e+04 |
| 846 | British Virgin Islands | VGB | 2010 | 2.755600e+04 |
| 847 | Brunei Darussalam | BRN | 2020 | 4.417250e+05 |
| 848 | Brunei Darussalam | BRN | 2019 | 4.380480e+05 |
| 849 | Brunei Darussalam | BRN | 2018 | 4.342740e+05 |
| 850 | Brunei Darussalam | BRN | 2017 | 4.302760e+05 |
| 851 | Brunei Darussalam | BRN | 2016 | 4.259940e+05 |
| 852 | Brunei Darussalam | BRN | 2015 | 4.214370e+05 |
| 853 | Brunei Darussalam | BRN | 2014 | 4.166560e+05 |
| 854 | Brunei Darussalam | BRN | 2013 | 4.117020e+05 |
| 855 | Brunei Darussalam | BRN | 2012 | 4.066340e+05 |
| 856 | Brunei Darussalam | BRN | 2011 | 4.015060e+05 |
| 857 | Brunei Darussalam | BRN | 2010 | 3.960530e+05 |
| 858 | Bulgaria | BGR | 2020 | 6.934015e+06 |
| 859 | Bulgaria | BGR | 2019 | 6.975761e+06 |
| 860 | Bulgaria | BGR | 2018 | 7.025037e+06 |
| 861 | Bulgaria | BGR | 2017 | 7.075947e+06 |
| 862 | Bulgaria | BGR | 2016 | 7.127822e+06 |
| 863 | Bulgaria | BGR | 2015 | 7.177991e+06 |
| 864 | Bulgaria | BGR | 2014 | 7.223938e+06 |
| 865 | Bulgaria | BGR | 2013 | 7.265115e+06 |
| 866 | Bulgaria | BGR | 2012 | 7.305888e+06 |
| 867 | Bulgaria | BGR | 2011 | 7.348328e+06 |
| 868 | Bulgaria | BGR | 2010 | 7.395599e+06 |
| 869 | Burkina Faso | BFA | 2020 | 2.152263e+07 |
| 870 | Burkina Faso | BFA | 2019 | 2.095164e+07 |
| 871 | Burkina Faso | BFA | 2018 | 2.039272e+07 |
| 872 | Burkina Faso | BFA | 2017 | 1.983586e+07 |
| 873 | Burkina Faso | BFA | 2016 | 1.927550e+07 |
| 874 | Burkina Faso | BFA | 2015 | 1.871802e+07 |
| 875 | Burkina Faso | BFA | 2014 | 1.816984e+07 |
| 876 | Burkina Faso | BFA | 2013 | 1.763641e+07 |
| 877 | Burkina Faso | BFA | 2012 | 1.711373e+07 |
| 878 | Burkina Faso | BFA | 2011 | 1.660265e+07 |
| 879 | Burkina Faso | BFA | 2010 | 1.611684e+07 |
| 880 | Burundi | BDI | 2020 | 1.222023e+07 |
| 881 | Burundi | BDI | 2019 | 1.187484e+07 |
| 882 | Burundi | BDI | 2018 | 1.149347e+07 |
| 883 | Burundi | BDI | 2017 | 1.115559e+07 |
| 884 | Burundi | BDI | 2016 | 1.090333e+07 |
| 885 | Burundi | BDI | 2015 | 1.072715e+07 |
| 886 | Burundi | BDI | 2014 | 1.049491e+07 |
| 887 | Burundi | BDI | 2013 | 1.014958e+07 |
| 888 | Burundi | BDI | 2012 | 9.795479e+06 |
| 889 | Burundi | BDI | 2011 | 9.455733e+06 |
| 890 | Burundi | BDI | 2010 | 9.126605e+06 |
| 891 | Cabo Verde | CPV | 2020 | 5.826400e+05 |
| 892 | Cabo Verde | CPV | 2019 | 5.770300e+05 |
| 893 | Cabo Verde | CPV | 2018 | 5.712020e+05 |
| 894 | Cabo Verde | CPV | 2017 | 5.649540e+05 |
| 895 | Cabo Verde | CPV | 2016 | 5.583940e+05 |
| 896 | Cabo Verde | CPV | 2015 | 5.521660e+05 |
| 897 | Cabo Verde | CPV | 2014 | 5.460760e+05 |
| 898 | Cabo Verde | CPV | 2013 | 5.399400e+05 |
| 899 | Cabo Verde | CPV | 2012 | 5.338640e+05 |
| 900 | Cabo Verde | CPV | 2011 | 5.275210e+05 |
| 901 | Cabo Verde | CPV | 2010 | 5.212120e+05 |
| 902 | Cambodia | KHM | 2020 | 1.639686e+07 |
| 903 | Cambodia | KHM | 2019 | 1.620775e+07 |
| 904 | Cambodia | KHM | 2018 | 1.602524e+07 |
| 905 | Cambodia | KHM | 2017 | 1.583069e+07 |
| 906 | Cambodia | KHM | 2016 | 1.562458e+07 |
| 907 | Cambodia | KHM | 2015 | 1.541752e+07 |
| 908 | Cambodia | KHM | 2014 | 1.521082e+07 |
| 909 | Cambodia | KHM | 2013 | 1.499968e+07 |
| 910 | Cambodia | KHM | 2012 | 1.478664e+07 |
| 911 | Cambodia | KHM | 2011 | 1.457388e+07 |
| 912 | Cambodia | KHM | 2010 | 1.436353e+07 |
| 913 | Cameroon | CMR | 2020 | 2.649109e+07 |
| 914 | Cameroon | CMR | 2019 | 2.578234e+07 |
| 915 | Cameroon | CMR | 2018 | 2.507675e+07 |
| 916 | Cameroon | CMR | 2017 | 2.439318e+07 |
| 917 | Cameroon | CMR | 2016 | 2.371163e+07 |
| 918 | Cameroon | CMR | 2015 | 2.301265e+07 |
| 919 | Cameroon | CMR | 2014 | 2.229958e+07 |
| 920 | Cameroon | CMR | 2013 | 2.163285e+07 |
| 921 | Cameroon | CMR | 2012 | 2.103268e+07 |
| 922 | Cameroon | CMR | 2011 | 2.044887e+07 |
| 923 | Cameroon | CMR | 2010 | 1.987804e+07 |
| 924 | Canada | CAN | 2020 | 3.800717e+07 |
| 925 | Canada | CAN | 2019 | 3.760123e+07 |
| 926 | Canada | CAN | 2018 | 3.706508e+07 |
| 927 | Canada | CAN | 2017 | 3.654524e+07 |
| 928 | Canada | CAN | 2016 | 3.610949e+07 |
| 929 | Canada | CAN | 2015 | 3.570291e+07 |
| 930 | Canada | CAN | 2014 | 3.543744e+07 |
| 931 | Canada | CAN | 2013 | 3.508295e+07 |
| 932 | Canada | CAN | 2012 | 3.471422e+07 |
| 933 | Canada | CAN | 2011 | 3.433933e+07 |
| 934 | Canada | CAN | 2010 | 3.400489e+07 |
| 935 | Cayman Islands | CYM | 2020 | 6.731100e+04 |
| 936 | Cayman Islands | CYM | 2019 | 6.613400e+04 |
| 937 | Cayman Islands | CYM | 2018 | 6.488400e+04 |
| 938 | Cayman Islands | CYM | 2017 | 6.358100e+04 |
| 939 | Cayman Islands | CYM | 2016 | 6.225500e+04 |
| 940 | Cayman Islands | CYM | 2015 | 6.091100e+04 |
| 941 | Cayman Islands | CYM | 2014 | 5.955900e+04 |
| 942 | Cayman Islands | CYM | 2013 | 5.821200e+04 |
| 943 | Cayman Islands | CYM | 2012 | 5.686000e+04 |
| 944 | Cayman Islands | CYM | 2011 | 5.549200e+04 |
| 945 | Cayman Islands | CYM | 2010 | 5.407400e+04 |
| 946 | Central African Republic | CAF | 2020 | 5.343020e+06 |
| 947 | Central African Republic | CAF | 2019 | 5.209324e+06 |
| 948 | Central African Republic | CAF | 2018 | 5.094780e+06 |
| 949 | Central African Republic | CAF | 2017 | 4.996741e+06 |
| 950 | Central African Republic | CAF | 2016 | 4.904177e+06 |
| 951 | Central African Republic | CAF | 2015 | 4.819333e+06 |
| 952 | Central African Republic | CAF | 2014 | 4.798734e+06 |
| 953 | Central African Republic | CAF | 2013 | 4.802428e+06 |
| 954 | Central African Republic | CAF | 2012 | 4.773306e+06 |
| 955 | Central African Republic | CAF | 2011 | 4.732022e+06 |
| 956 | Central African Republic | CAF | 2010 | 4.660067e+06 |
| 957 | Chad | TCD | 2020 | 1.664470e+07 |
| 958 | Chad | TCD | 2019 | 1.612687e+07 |
| 959 | Chad | TCD | 2018 | 1.560421e+07 |
| 960 | Chad | TCD | 2017 | 1.508588e+07 |
| 961 | Chad | TCD | 2016 | 1.459258e+07 |
| 962 | Chad | TCD | 2015 | 1.414027e+07 |
| 963 | Chad | TCD | 2014 | 1.369713e+07 |
| 964 | Chad | TCD | 2013 | 1.321677e+07 |
| 965 | Chad | TCD | 2012 | 1.275491e+07 |
| 966 | Chad | TCD | 2011 | 1.231773e+07 |
| 967 | Chad | TCD | 2010 | 1.189473e+07 |
| 968 | Channel Islands | CHI | 2020 | 1.711130e+05 |
| 969 | Channel Islands | CHI | 2019 | 1.694100e+05 |
| 970 | Channel Islands | CHI | 2018 | 1.672590e+05 |
| 971 | Channel Islands | CHI | 2017 | 1.652150e+05 |
| 972 | Channel Islands | CHI | 2016 | 1.637210e+05 |
| 973 | Channel Islands | CHI | 2015 | 1.621900e+05 |
| 974 | Channel Islands | CHI | 2014 | 1.609120e+05 |
| 975 | Channel Islands | CHI | 2013 | 1.597940e+05 |
| 976 | Channel Islands | CHI | 2012 | 1.586210e+05 |
| 977 | Channel Islands | CHI | 2011 | 1.578190e+05 |
| 978 | Channel Islands | CHI | 2010 | 1.569330e+05 |
| 979 | Chile | CHL | 2020 | 1.930032e+07 |
| 980 | Chile | CHL | 2019 | 1.903948e+07 |
| 981 | Chile | CHL | 2018 | 1.870145e+07 |
| 982 | Chile | CHL | 2017 | 1.836858e+07 |
| 983 | Chile | CHL | 2016 | 1.808388e+07 |
| 984 | Chile | CHL | 2015 | 1.787012e+07 |
| 985 | Chile | CHL | 2014 | 1.768711e+07 |
| 986 | Chile | CHL | 2013 | 1.750992e+07 |
| 987 | Chile | CHL | 2012 | 1.734177e+07 |
| 988 | Chile | CHL | 2011 | 1.717357e+07 |
| 989 | Chile | CHL | 2010 | 1.700416e+07 |
| 990 | China | CHN | 2020 | 1.411100e+09 |
| 991 | China | CHN | 2019 | 1.407745e+09 |
| 992 | China | CHN | 2018 | 1.402760e+09 |
| 993 | China | CHN | 2017 | 1.396215e+09 |
| 994 | China | CHN | 2016 | 1.387790e+09 |
| 995 | China | CHN | 2015 | 1.379860e+09 |
| 996 | China | CHN | 2014 | 1.371860e+09 |
| 997 | China | CHN | 2013 | 1.363240e+09 |
| 998 | China | CHN | 2012 | 1.354190e+09 |
| 999 | China | CHN | 2011 | 1.345035e+09 |
| 1000 | China | CHN | 2010 | 1.337705e+09 |
| 1001 | Colombia | COL | 2020 | 5.093066e+07 |
| 1002 | Colombia | COL | 2019 | 5.018741e+07 |
| 1003 | Colombia | COL | 2018 | 4.927696e+07 |
| 1004 | Colombia | COL | 2017 | 4.835167e+07 |
| 1005 | Colombia | COL | 2016 | 4.762596e+07 |
| 1006 | Colombia | COL | 2015 | 4.711973e+07 |
| 1007 | Colombia | COL | 2014 | 4.667795e+07 |
| 1008 | Colombia | COL | 2013 | 4.623793e+07 |
| 1009 | Colombia | COL | 2012 | 4.578242e+07 |
| 1010 | Colombia | COL | 2011 | 4.530890e+07 |
| 1011 | Colombia | COL | 2010 | 4.481611e+07 |
| 1012 | Comoros | COM | 2020 | 8.061660e+05 |
| 1013 | Comoros | COM | 2019 | 7.909860e+05 |
| 1014 | Comoros | COM | 2018 | 7.763130e+05 |
| 1015 | Comoros | COM | 2017 | 7.616640e+05 |
| 1016 | Comoros | COM | 2016 | 7.462320e+05 |
| 1017 | Comoros | COM | 2015 | 7.302160e+05 |
| 1018 | Comoros | COM | 2014 | 7.146120e+05 |
| 1019 | Comoros | COM | 2013 | 6.993930e+05 |
| 1020 | Comoros | COM | 2012 | 6.845530e+05 |
| 1021 | Comoros | COM | 2011 | 6.700710e+05 |
| 1022 | Comoros | COM | 2010 | 6.560240e+05 |
| 1023 | Congo, Dem. Rep. | COD | 2020 | 9.285316e+07 |
| 1024 | Congo, Dem. Rep. | COD | 2019 | 8.990689e+07 |
| 1025 | Congo, Dem. Rep. | COD | 2018 | 8.708736e+07 |
| 1026 | Congo, Dem. Rep. | COD | 2017 | 8.428327e+07 |
| 1027 | Congo, Dem. Rep. | COD | 2016 | 8.143098e+07 |
| 1028 | Congo, Dem. Rep. | COD | 2015 | 7.865690e+07 |
| 1029 | Congo, Dem. Rep. | COD | 2014 | 7.603559e+07 |
| 1030 | Congo, Dem. Rep. | COD | 2013 | 7.346002e+07 |
| 1031 | Congo, Dem. Rep. | COD | 2012 | 7.099787e+07 |
| 1032 | Congo, Dem. Rep. | COD | 2011 | 6.865427e+07 |
| 1033 | Congo, Dem. Rep. | COD | 2010 | 6.639126e+07 |
| 1034 | Congo, Rep. | COG | 2020 | 5.702174e+06 |
| 1035 | Congo, Rep. | COG | 2019 | 5.570733e+06 |
| 1036 | Congo, Rep. | COG | 2018 | 5.441062e+06 |
| 1037 | Congo, Rep. | COG | 2017 | 5.312340e+06 |
| 1038 | Congo, Rep. | COG | 2016 | 5.186824e+06 |
| 1039 | Congo, Rep. | COG | 2015 | 5.064386e+06 |
| 1040 | Congo, Rep. | COG | 2014 | 4.944861e+06 |
| 1041 | Congo, Rep. | COG | 2013 | 4.828066e+06 |
| 1042 | Congo, Rep. | COG | 2012 | 4.713257e+06 |
| 1043 | Congo, Rep. | COG | 2011 | 4.584216e+06 |
| 1044 | Congo, Rep. | COG | 2010 | 4.437884e+06 |
| 1045 | Costa Rica | CRI | 2020 | 5.123105e+06 |
| 1046 | Costa Rica | CRI | 2019 | 5.084532e+06 |
| 1047 | Costa Rica | CRI | 2018 | 5.040734e+06 |
| 1048 | Costa Rica | CRI | 2017 | 4.993842e+06 |
| 1049 | Costa Rica | CRI | 2016 | 4.945205e+06 |
| 1050 | Costa Rica | CRI | 2015 | 4.895242e+06 |
| 1051 | Costa Rica | CRI | 2014 | 4.844288e+06 |
| 1052 | Costa Rica | CRI | 2013 | 4.791535e+06 |
| 1053 | Costa Rica | CRI | 2012 | 4.736593e+06 |
| 1054 | Costa Rica | CRI | 2011 | 4.679926e+06 |
| 1055 | Costa Rica | CRI | 2010 | 4.622252e+06 |
| 1056 | Cote d'Ivoire | CIV | 2020 | 2.681179e+07 |
| 1057 | Cote d'Ivoire | CIV | 2019 | 2.614755e+07 |
| 1058 | Cote d'Ivoire | CIV | 2018 | 2.549399e+07 |
| 1059 | Cote d'Ivoire | CIV | 2017 | 2.484802e+07 |
| 1060 | Cote d'Ivoire | CIV | 2016 | 2.421362e+07 |
| 1061 | Cote d'Ivoire | CIV | 2015 | 2.359674e+07 |
| 1062 | Cote d'Ivoire | CIV | 2014 | 2.299556e+07 |
| 1063 | Cote d'Ivoire | CIV | 2013 | 2.246927e+07 |
| 1064 | Cote d'Ivoire | CIV | 2012 | 2.201071e+07 |
| 1065 | Cote d'Ivoire | CIV | 2011 | 2.156291e+07 |
| 1066 | Cote d'Ivoire | CIV | 2010 | 2.112004e+07 |
| 1067 | Croatia | HRV | 2020 | 4.047680e+06 |
| 1068 | Croatia | HRV | 2019 | 4.065253e+06 |
| 1069 | Croatia | HRV | 2018 | 4.087843e+06 |
| 1070 | Croatia | HRV | 2017 | 4.124531e+06 |
| 1071 | Croatia | HRV | 2016 | 4.174349e+06 |
| 1072 | Croatia | HRV | 2015 | 4.203604e+06 |
| 1073 | Croatia | HRV | 2014 | 4.238389e+06 |
| 1074 | Croatia | HRV | 2013 | 4.255689e+06 |
| 1075 | Croatia | HRV | 2012 | 4.267558e+06 |
| 1076 | Croatia | HRV | 2011 | 4.280622e+06 |
| 1077 | Croatia | HRV | 2010 | 4.295427e+06 |
| 1078 | Cuba | CUB | 2020 | 1.130070e+07 |
| 1079 | Cuba | CUB | 2019 | 1.131670e+07 |
| 1080 | Cuba | CUB | 2018 | 1.132824e+07 |
| 1081 | Cuba | CUB | 2017 | 1.133640e+07 |
| 1082 | Cuba | CUB | 2016 | 1.134201e+07 |
| 1083 | Cuba | CUB | 2015 | 1.133989e+07 |
| 1084 | Cuba | CUB | 2014 | 1.133203e+07 |
| 1085 | Cuba | CUB | 2013 | 1.132158e+07 |
| 1086 | Cuba | CUB | 2012 | 1.130929e+07 |
| 1087 | Cuba | CUB | 2011 | 1.129871e+07 |
| 1088 | Cuba | CUB | 2010 | 1.129042e+07 |
| 1089 | Curacao | CUW | 2020 | 1.549470e+05 |
| 1090 | Curacao | CUW | 2019 | 1.574410e+05 |
| 1091 | Curacao | CUW | 2018 | 1.593360e+05 |
| 1092 | Curacao | CUW | 2017 | 1.601750e+05 |
| 1093 | Curacao | CUW | 2016 | 1.596640e+05 |
| 1094 | Curacao | CUW | 2015 | 1.579800e+05 |
| 1095 | Curacao | CUW | 2014 | 1.559090e+05 |
| 1096 | Curacao | CUW | 2013 | 1.538220e+05 |
| 1097 | Curacao | CUW | 2012 | 1.520880e+05 |
| 1098 | Curacao | CUW | 2011 | 1.508310e+05 |
| 1099 | Curacao | CUW | 2010 | 1.487030e+05 |
| 1100 | Cyprus | CYP | 2020 | 1.237537e+06 |
| 1101 | Cyprus | CYP | 2019 | 1.228836e+06 |
| 1102 | Cyprus | CYP | 2018 | 1.218831e+06 |
| 1103 | Cyprus | CYP | 2017 | 1.208523e+06 |
| 1104 | Cyprus | CYP | 2016 | 1.197881e+06 |
| 1105 | Cyprus | CYP | 2015 | 1.187280e+06 |
| 1106 | Cyprus | CYP | 2014 | 1.176995e+06 |
| 1107 | Cyprus | CYP | 2013 | 1.166968e+06 |
| 1108 | Cyprus | CYP | 2012 | 1.156556e+06 |
| 1109 | Cyprus | CYP | 2011 | 1.145086e+06 |
| 1110 | Cyprus | CYP | 2010 | 1.129686e+06 |
| 1111 | Czechia | CZE | 2020 | 1.069786e+07 |
| 1112 | Czechia | CZE | 2019 | 1.067187e+07 |
| 1113 | Czechia | CZE | 2018 | 1.062993e+07 |
| 1114 | Czechia | CZE | 2017 | 1.059444e+07 |
| 1115 | Czechia | CZE | 2016 | 1.056633e+07 |
| 1116 | Czechia | CZE | 2015 | 1.054606e+07 |
| 1117 | Czechia | CZE | 2014 | 1.052535e+07 |
| 1118 | Czechia | CZE | 2013 | 1.051427e+07 |
| 1119 | Czechia | CZE | 2012 | 1.051078e+07 |
| 1120 | Czechia | CZE | 2011 | 1.049609e+07 |
| 1121 | Czechia | CZE | 2010 | 1.047441e+07 |
| 1122 | Denmark | DNK | 2020 | 5.831404e+06 |
| 1123 | Denmark | DNK | 2019 | 5.814422e+06 |
| 1124 | Denmark | DNK | 2018 | 5.793636e+06 |
| 1125 | Denmark | DNK | 2017 | 5.764980e+06 |
| 1126 | Denmark | DNK | 2016 | 5.728010e+06 |
| 1127 | Denmark | DNK | 2015 | 5.683483e+06 |
| 1128 | Denmark | DNK | 2014 | 5.643475e+06 |
| 1129 | Denmark | DNK | 2013 | 5.614932e+06 |
| 1130 | Denmark | DNK | 2012 | 5.591572e+06 |
| 1131 | Denmark | DNK | 2011 | 5.570572e+06 |
| 1132 | Denmark | DNK | 2010 | 5.547683e+06 |
| 1133 | Djibouti | DJI | 2020 | 1.090156e+06 |
| 1134 | Djibouti | DJI | 2019 | 1.073994e+06 |
| 1135 | Djibouti | DJI | 2018 | 1.057198e+06 |
| 1136 | Djibouti | DJI | 2017 | 1.040233e+06 |
| 1137 | Djibouti | DJI | 2016 | 1.023261e+06 |
| 1138 | Djibouti | DJI | 2015 | 1.006259e+06 |
| 1139 | Djibouti | DJI | 2014 | 9.890870e+05 |
| 1140 | Djibouti | DJI | 2013 | 9.717530e+05 |
| 1141 | Djibouti | DJI | 2012 | 9.542970e+05 |
| 1142 | Djibouti | DJI | 2011 | 9.368110e+05 |
| 1143 | Djibouti | DJI | 2010 | 9.191990e+05 |
| 1144 | Dominica | DMA | 2020 | 7.199500e+04 |
| 1145 | Dominica | DMA | 2019 | 7.142800e+04 |
| 1146 | Dominica | DMA | 2018 | 7.082300e+04 |
| 1147 | Dominica | DMA | 2017 | 7.040300e+04 |
| 1148 | Dominica | DMA | 2016 | 7.007500e+04 |
| 1149 | Dominica | DMA | 2015 | 7.000700e+04 |
| 1150 | Dominica | DMA | 2014 | 6.937100e+04 |
| 1151 | Dominica | DMA | 2013 | 6.881900e+04 |
| 1152 | Dominica | DMA | 2012 | 6.888800e+04 |
| 1153 | Dominica | DMA | 2011 | 6.874200e+04 |
| 1154 | Dominica | DMA | 2010 | 6.875500e+04 |
| 1155 | Dominican Republic | DOM | 2020 | 1.099966e+07 |
| 1156 | Dominican Republic | DOM | 2019 | 1.088188e+07 |
| 1157 | Dominican Republic | DOM | 2018 | 1.076553e+07 |
| 1158 | Dominican Republic | DOM | 2017 | 1.064724e+07 |
| 1159 | Dominican Republic | DOM | 2016 | 1.052759e+07 |
| 1160 | Dominican Republic | DOM | 2015 | 1.040583e+07 |
| 1161 | Dominican Republic | DOM | 2014 | 1.028212e+07 |
| 1162 | Dominican Republic | DOM | 2013 | 1.015705e+07 |
| 1163 | Dominican Republic | DOM | 2012 | 1.003088e+07 |
| 1164 | Dominican Republic | DOM | 2011 | 9.903737e+06 |
| 1165 | Dominican Republic | DOM | 2010 | 9.775755e+06 |
| 1166 | Ecuador | ECU | 2020 | 1.758860e+07 |
| 1167 | Ecuador | ECU | 2019 | 1.734374e+07 |
| 1168 | Ecuador | ECU | 2018 | 1.701567e+07 |
| 1169 | Ecuador | ECU | 2017 | 1.669694e+07 |
| 1170 | Ecuador | ECU | 2016 | 1.643958e+07 |
| 1171 | Ecuador | ECU | 2015 | 1.619590e+07 |
| 1172 | Ecuador | ECU | 2014 | 1.595799e+07 |
| 1173 | Ecuador | ECU | 2013 | 1.572299e+07 |
| 1174 | Ecuador | ECU | 2012 | 1.548388e+07 |
| 1175 | Ecuador | ECU | 2011 | 1.523773e+07 |
| 1176 | Ecuador | ECU | 2010 | 1.498958e+07 |
| 1177 | Egypt, Arab Rep. | EGY | 2020 | 1.074651e+08 |
| 1178 | Egypt, Arab Rep. | EGY | 2019 | 1.056187e+08 |
| 1179 | Egypt, Arab Rep. | EGY | 2018 | 1.037408e+08 |
| 1180 | Egypt, Arab Rep. | EGY | 2017 | 1.017894e+08 |
| 1181 | Egypt, Arab Rep. | EGY | 2016 | 9.978403e+07 |
| 1182 | Egypt, Arab Rep. | EGY | 2015 | 9.772380e+07 |
| 1183 | Egypt, Arab Rep. | EGY | 2014 | 9.559232e+07 |
| 1184 | Egypt, Arab Rep. | EGY | 2013 | 9.337789e+07 |
| 1185 | Egypt, Arab Rep. | EGY | 2012 | 9.124038e+07 |
| 1186 | Egypt, Arab Rep. | EGY | 2011 | 8.920005e+07 |
| 1187 | Egypt, Arab Rep. | EGY | 2010 | 8.725241e+07 |
| 1188 | El Salvador | SLV | 2020 | 6.292731e+06 |
| 1189 | El Salvador | SLV | 2019 | 6.280217e+06 |
| 1190 | El Salvador | SLV | 2018 | 6.276342e+06 |
| 1191 | El Salvador | SLV | 2017 | 6.266654e+06 |
| 1192 | El Salvador | SLV | 2016 | 6.250510e+06 |
| 1193 | El Salvador | SLV | 2015 | 6.231066e+06 |
| 1194 | El Salvador | SLV | 2014 | 6.209526e+06 |
| 1195 | El Salvador | SLV | 2013 | 6.185642e+06 |
| 1196 | El Salvador | SLV | 2012 | 6.161289e+06 |
| 1197 | El Salvador | SLV | 2011 | 6.137349e+06 |
| 1198 | El Salvador | SLV | 2010 | 6.114034e+06 |
| 1199 | Equatorial Guinea | GNQ | 2020 | 1.596049e+06 |
| 1200 | Equatorial Guinea | GNQ | 2019 | 1.553031e+06 |
| 1201 | Equatorial Guinea | GNQ | 2018 | 1.502091e+06 |
| 1202 | Equatorial Guinea | GNQ | 2017 | 1.450694e+06 |
| 1203 | Equatorial Guinea | GNQ | 2016 | 1.398927e+06 |
| 1204 | Equatorial Guinea | GNQ | 2015 | 1.346973e+06 |
| 1205 | Equatorial Guinea | GNQ | 2014 | 1.295183e+06 |
| 1206 | Equatorial Guinea | GNQ | 2013 | 1.243941e+06 |
| 1207 | Equatorial Guinea | GNQ | 2012 | 1.193636e+06 |
| 1208 | Equatorial Guinea | GNQ | 2011 | 1.144588e+06 |
| 1209 | Equatorial Guinea | GNQ | 2010 | 1.094524e+06 |
| 1210 | Eritrea | ERI | 2020 | 3.555868e+06 |
| 1211 | Eritrea | ERI | 2019 | 3.498818e+06 |
| 1212 | Eritrea | ERI | 2018 | 3.445374e+06 |
| 1213 | Eritrea | ERI | 2017 | 3.396933e+06 |
| 1214 | Eritrea | ERI | 2016 | 3.365287e+06 |
| 1215 | Eritrea | ERI | 2015 | 3.340006e+06 |
| 1216 | Eritrea | ERI | 2014 | 3.323425e+06 |
| 1217 | Eritrea | ERI | 2013 | 3.296367e+06 |
| 1218 | Eritrea | ERI | 2012 | 3.252596e+06 |
| 1219 | Eritrea | ERI | 2011 | 3.207570e+06 |
| 1220 | Eritrea | ERI | 2010 | 3.147727e+06 |
| 1221 | Estonia | EST | 2020 | 1.329522e+06 |
| 1222 | Estonia | EST | 2019 | 1.326898e+06 |
| 1223 | Estonia | EST | 2018 | 1.321977e+06 |
| 1224 | Estonia | EST | 2017 | 1.317384e+06 |
| 1225 | Estonia | EST | 2016 | 1.315790e+06 |
| 1226 | Estonia | EST | 2015 | 1.315407e+06 |
| 1227 | Estonia | EST | 2014 | 1.314545e+06 |
| 1228 | Estonia | EST | 2013 | 1.317997e+06 |
| 1229 | Estonia | EST | 2012 | 1.322696e+06 |
| 1230 | Estonia | EST | 2011 | 1.327439e+06 |
| 1231 | Estonia | EST | 2010 | 1.331475e+06 |
| 1232 | Eswatini | SWZ | 2020 | 1.180655e+06 |
| 1233 | Eswatini | SWZ | 2019 | 1.169613e+06 |
| 1234 | Eswatini | SWZ | 2018 | 1.160428e+06 |
| 1235 | Eswatini | SWZ | 2017 | 1.151390e+06 |
| 1236 | Eswatini | SWZ | 2016 | 1.142524e+06 |
| 1237 | Eswatini | SWZ | 2015 | 1.133936e+06 |
| 1238 | Eswatini | SWZ | 2014 | 1.125865e+06 |
| 1239 | Eswatini | SWZ | 2013 | 1.118319e+06 |
| 1240 | Eswatini | SWZ | 2012 | 1.111444e+06 |
| 1241 | Eswatini | SWZ | 2011 | 1.105371e+06 |
| 1242 | Eswatini | SWZ | 2010 | 1.099920e+06 |
| 1243 | Ethiopia | ETH | 2020 | 1.171909e+08 |
| 1244 | Ethiopia | ETH | 2019 | 1.141206e+08 |
| 1245 | Ethiopia | ETH | 2018 | 1.111294e+08 |
| 1246 | Ethiopia | ETH | 2017 | 1.081980e+08 |
| 1247 | Ethiopia | ETH | 2016 | 1.052932e+08 |
| 1248 | Ethiopia | ETH | 2015 | 1.024719e+08 |
| 1249 | Ethiopia | ETH | 2014 | 9.974677e+07 |
| 1250 | Ethiopia | ETH | 2013 | 9.708437e+07 |
| 1251 | Ethiopia | ETH | 2012 | 9.445128e+07 |
| 1252 | Ethiopia | ETH | 2011 | 9.181793e+07 |
| 1253 | Ethiopia | ETH | 2010 | 8.923779e+07 |
| 1254 | Faroe Islands | FRO | 2020 | 5.241500e+04 |
| 1255 | Faroe Islands | FRO | 2019 | 5.168100e+04 |
| 1256 | Faroe Islands | FRO | 2018 | 5.095500e+04 |
| 1257 | Faroe Islands | FRO | 2017 | 5.023000e+04 |
| 1258 | Faroe Islands | FRO | 2016 | 4.950000e+04 |
| 1259 | Faroe Islands | FRO | 2015 | 4.881600e+04 |
| 1260 | Faroe Islands | FRO | 2014 | 4.846500e+04 |
| 1261 | Faroe Islands | FRO | 2013 | 4.841800e+04 |
| 1262 | Faroe Islands | FRO | 2012 | 4.839200e+04 |
| 1263 | Faroe Islands | FRO | 2011 | 4.838600e+04 |
| 1264 | Faroe Islands | FRO | 2010 | 4.841000e+04 |
| 1265 | Fiji | FJI | 2020 | 9.204220e+05 |
| 1266 | Fiji | FJI | 2019 | 9.184650e+05 |
| 1267 | Fiji | FJI | 2018 | 9.189960e+05 |
| 1268 | Fiji | FJI | 2017 | 9.190190e+05 |
| 1269 | Fiji | FJI | 2016 | 9.183710e+05 |
| 1270 | Fiji | FJI | 2015 | 9.172000e+05 |
| 1271 | Fiji | FJI | 2014 | 9.155600e+05 |
| 1272 | Fiji | FJI | 2013 | 9.134530e+05 |
| 1273 | Fiji | FJI | 2012 | 9.110590e+05 |
| 1274 | Fiji | FJI | 2011 | 9.083550e+05 |
| 1275 | Fiji | FJI | 2010 | 9.051690e+05 |
| 1276 | Finland | FIN | 2020 | 5.529543e+06 |
| 1277 | Finland | FIN | 2019 | 5.521606e+06 |
| 1278 | Finland | FIN | 2018 | 5.515525e+06 |
| 1279 | Finland | FIN | 2017 | 5.508214e+06 |
| 1280 | Finland | FIN | 2016 | 5.495303e+06 |
| 1281 | Finland | FIN | 2015 | 5.479531e+06 |
| 1282 | Finland | FIN | 2014 | 5.461512e+06 |
| 1283 | Finland | FIN | 2013 | 5.438972e+06 |
| 1284 | Finland | FIN | 2012 | 5.413971e+06 |
| 1285 | Finland | FIN | 2011 | 5.388272e+06 |
| 1286 | Finland | FIN | 2010 | 5.363352e+06 |
| 1287 | France | FRA | 2020 | 6.757111e+07 |
| 1288 | France | FRA | 2019 | 6.738800e+07 |
| 1289 | France | FRA | 2018 | 6.715835e+07 |
| 1290 | France | FRA | 2017 | 6.691802e+07 |
| 1291 | France | FRA | 2016 | 6.672410e+07 |
| 1292 | France | FRA | 2015 | 6.654827e+07 |
| 1293 | France | FRA | 2014 | 6.631207e+07 |
| 1294 | France | FRA | 2013 | 6.600229e+07 |
| 1295 | France | FRA | 2012 | 6.566224e+07 |
| 1296 | France | FRA | 2011 | 6.534523e+07 |
| 1297 | France | FRA | 2010 | 6.503058e+07 |
| 1298 | French Polynesia | PYF | 2020 | 3.019200e+05 |
| 1299 | French Polynesia | PYF | 2019 | 2.997170e+05 |
| 1300 | French Polynesia | PYF | 2018 | 2.976060e+05 |
| 1301 | French Polynesia | PYF | 2017 | 2.954500e+05 |
| 1302 | French Polynesia | PYF | 2016 | 2.935410e+05 |
| 1303 | French Polynesia | PYF | 2015 | 2.917870e+05 |
| 1304 | French Polynesia | PYF | 2014 | 2.898730e+05 |
| 1305 | French Polynesia | PYF | 2013 | 2.880320e+05 |
| 1306 | French Polynesia | PYF | 2012 | 2.865840e+05 |
| 1307 | French Polynesia | PYF | 2011 | 2.852650e+05 |
| 1308 | French Polynesia | PYF | 2010 | 2.837880e+05 |
| 1309 | Gabon | GAB | 2020 | 2.292573e+06 |
| 1310 | Gabon | GAB | 2019 | 2.242785e+06 |
| 1311 | Gabon | GAB | 2018 | 2.192012e+06 |
| 1312 | Gabon | GAB | 2017 | 2.140215e+06 |
| 1313 | Gabon | GAB | 2016 | 2.086206e+06 |
| 1314 | Gabon | GAB | 2015 | 2.028517e+06 |
| 1315 | Gabon | GAB | 2014 | 1.966855e+06 |
| 1316 | Gabon | GAB | 2013 | 1.902226e+06 |
| 1317 | Gabon | GAB | 2012 | 1.836705e+06 |
| 1318 | Gabon | GAB | 2011 | 1.772500e+06 |
| 1319 | Gabon | GAB | 2010 | 1.711105e+06 |
| 1320 | Gambia, The | GMB | 2020 | 2.573995e+06 |
| 1321 | Gambia, The | GMB | 2019 | 2.508883e+06 |
| 1322 | Gambia, The | GMB | 2018 | 2.444916e+06 |
| 1323 | Gambia, The | GMB | 2017 | 2.381182e+06 |
| 1324 | Gambia, The | GMB | 2016 | 2.317206e+06 |
| 1325 | Gambia, The | GMB | 2015 | 2.253133e+06 |
| 1326 | Gambia, The | GMB | 2014 | 2.189019e+06 |
| 1327 | Gambia, The | GMB | 2013 | 2.124869e+06 |
| 1328 | Gambia, The | GMB | 2012 | 2.061014e+06 |
| 1329 | Gambia, The | GMB | 2011 | 1.998212e+06 |
| 1330 | Gambia, The | GMB | 2010 | 1.937275e+06 |
| 1331 | Georgia | GEO | 2020 | 3.722716e+06 |
| 1332 | Georgia | GEO | 2019 | 3.720161e+06 |
| 1333 | Georgia | GEO | 2018 | 3.726549e+06 |
| 1334 | Georgia | GEO | 2017 | 3.728004e+06 |
| 1335 | Georgia | GEO | 2016 | 3.727505e+06 |
| 1336 | Georgia | GEO | 2015 | 3.725276e+06 |
| 1337 | Georgia | GEO | 2014 | 3.719414e+06 |
| 1338 | Georgia | GEO | 2013 | 3.717668e+06 |
| 1339 | Georgia | GEO | 2012 | 3.728874e+06 |
| 1340 | Georgia | GEO | 2011 | 3.756441e+06 |
| 1341 | Georgia | GEO | 2010 | 3.786695e+06 |
| 1342 | Germany | DEU | 2020 | 8.316087e+07 |
| 1343 | Germany | DEU | 2019 | 8.309296e+07 |
| 1344 | Germany | DEU | 2018 | 8.290578e+07 |
| 1345 | Germany | DEU | 2017 | 8.265700e+07 |
| 1346 | Germany | DEU | 2016 | 8.234867e+07 |
| 1347 | Germany | DEU | 2015 | 8.168661e+07 |
| 1348 | Germany | DEU | 2014 | 8.098250e+07 |
| 1349 | Germany | DEU | 2013 | 8.064560e+07 |
| 1350 | Germany | DEU | 2012 | 8.042582e+07 |
| 1351 | Germany | DEU | 2011 | 8.027498e+07 |
| 1352 | Germany | DEU | 2010 | 8.177693e+07 |
| 1353 | Ghana | GHA | 2020 | 3.218040e+07 |
| 1354 | Ghana | GHA | 2019 | 3.152229e+07 |
| 1355 | Ghana | GHA | 2018 | 3.087064e+07 |
| 1356 | Ghana | GHA | 2017 | 3.022226e+07 |
| 1357 | Ghana | GHA | 2016 | 2.955430e+07 |
| 1358 | Ghana | GHA | 2015 | 2.887094e+07 |
| 1359 | Ghana | GHA | 2014 | 2.819636e+07 |
| 1360 | Ghana | GHA | 2013 | 2.752560e+07 |
| 1361 | Ghana | GHA | 2012 | 2.685876e+07 |
| 1362 | Ghana | GHA | 2011 | 2.620594e+07 |
| 1363 | Ghana | GHA | 2010 | 2.557472e+07 |
| 1364 | Gibraltar | GIB | 2020 | 3.270900e+04 |
| 1365 | Gibraltar | GIB | 2019 | 3.268500e+04 |
| 1366 | Gibraltar | GIB | 2018 | 3.264800e+04 |
| 1367 | Gibraltar | GIB | 2017 | 3.260200e+04 |
| 1368 | Gibraltar | GIB | 2016 | 3.256500e+04 |
| 1369 | Gibraltar | GIB | 2015 | 3.252000e+04 |
| 1370 | Gibraltar | GIB | 2014 | 3.245200e+04 |
| 1371 | Gibraltar | GIB | 2013 | 3.241100e+04 |
| 1372 | Gibraltar | GIB | 2012 | 3.216000e+04 |
| 1373 | Gibraltar | GIB | 2011 | 3.170100e+04 |
| 1374 | Gibraltar | GIB | 2010 | 3.126200e+04 |
| 1375 | Greece | GRC | 2020 | 1.069860e+07 |
| 1376 | Greece | GRC | 2019 | 1.072158e+07 |
| 1377 | Greece | GRC | 2018 | 1.073288e+07 |
| 1378 | Greece | GRC | 2017 | 1.075468e+07 |
| 1379 | Greece | GRC | 2016 | 1.077597e+07 |
| 1380 | Greece | GRC | 2015 | 1.082088e+07 |
| 1381 | Greece | GRC | 2014 | 1.089241e+07 |
| 1382 | Greece | GRC | 2013 | 1.096521e+07 |
| 1383 | Greece | GRC | 2012 | 1.104501e+07 |
| 1384 | Greece | GRC | 2011 | 1.110490e+07 |
| 1385 | Greece | GRC | 2010 | 1.112134e+07 |
| 1386 | Greenland | GRL | 2020 | 5.636700e+04 |
| 1387 | Greenland | GRL | 2019 | 5.622500e+04 |
| 1388 | Greenland | GRL | 2018 | 5.602300e+04 |
| 1389 | Greenland | GRL | 2017 | 5.617200e+04 |
| 1390 | Greenland | GRL | 2016 | 5.618600e+04 |
| 1391 | Greenland | GRL | 2015 | 5.611400e+04 |
| 1392 | Greenland | GRL | 2014 | 5.629500e+04 |
| 1393 | Greenland | GRL | 2013 | 5.648300e+04 |
| 1394 | Greenland | GRL | 2012 | 5.681000e+04 |
| 1395 | Greenland | GRL | 2011 | 5.689000e+04 |
| 1396 | Greenland | GRL | 2010 | 5.690500e+04 |
| 1397 | Grenada | GRD | 2020 | 1.236630e+05 |
| 1398 | Grenada | GRD | 2019 | 1.227240e+05 |
| 1399 | Grenada | GRD | 2018 | 1.218380e+05 |
| 1400 | Grenada | GRD | 2017 | 1.209210e+05 |
| 1401 | Grenada | GRD | 2016 | 1.199660e+05 |
| 1402 | Grenada | GRD | 2015 | 1.189800e+05 |
| 1403 | Grenada | GRD | 2014 | 1.179720e+05 |
| 1404 | Grenada | GRD | 2013 | 1.169450e+05 |
| 1405 | Grenada | GRD | 2012 | 1.159120e+05 |
| 1406 | Grenada | GRD | 2011 | 1.149180e+05 |
| 1407 | Grenada | GRD | 2010 | 1.140390e+05 |
| 1408 | Guam | GUM | 2020 | 1.692310e+05 |
| 1409 | Guam | GUM | 2019 | 1.686240e+05 |
| 1410 | Guam | GUM | 2018 | 1.686780e+05 |
| 1411 | Guam | GUM | 2017 | 1.686060e+05 |
| 1412 | Guam | GUM | 2016 | 1.683460e+05 |
| 1413 | Guam | GUM | 2015 | 1.679780e+05 |
| 1414 | Guam | GUM | 2014 | 1.675430e+05 |
| 1415 | Guam | GUM | 2013 | 1.670540e+05 |
| 1416 | Guam | GUM | 2012 | 1.663920e+05 |
| 1417 | Guam | GUM | 2011 | 1.656490e+05 |
| 1418 | Guam | GUM | 2010 | 1.649050e+05 |
| 1419 | Guatemala | GTM | 2020 | 1.685833e+07 |
| 1420 | Guatemala | GTM | 2019 | 1.660403e+07 |
| 1421 | Guatemala | GTM | 2018 | 1.634695e+07 |
| 1422 | Guatemala | GTM | 2017 | 1.608742e+07 |
| 1423 | Guatemala | GTM | 2016 | 1.582769e+07 |
| 1424 | Guatemala | GTM | 2015 | 1.556742e+07 |
| 1425 | Guatemala | GTM | 2014 | 1.530632e+07 |
| 1426 | Guatemala | GTM | 2013 | 1.504398e+07 |
| 1427 | Guatemala | GTM | 2012 | 1.478194e+07 |
| 1428 | Guatemala | GTM | 2011 | 1.452152e+07 |
| 1429 | Guatemala | GTM | 2010 | 1.425969e+07 |
| 1430 | Guinea | GIN | 2020 | 1.320515e+07 |
| 1431 | Guinea | GIN | 2019 | 1.287754e+07 |
| 1432 | Guinea | GIN | 2018 | 1.255486e+07 |
| 1433 | Guinea | GIN | 2017 | 1.224079e+07 |
| 1434 | Guinea | GIN | 2016 | 1.193098e+07 |
| 1435 | Guinea | GIN | 2015 | 1.162600e+07 |
| 1436 | Guinea | GIN | 2014 | 1.133336e+07 |
| 1437 | Guinea | GIN | 2013 | 1.105543e+07 |
| 1438 | Guinea | GIN | 2012 | 1.078869e+07 |
| 1439 | Guinea | GIN | 2011 | 1.052771e+07 |
| 1440 | Guinea | GIN | 2010 | 1.027073e+07 |
| 1441 | Guinea-Bissau | GNB | 2020 | 2.015828e+06 |
| 1442 | Guinea-Bissau | GNB | 2019 | 1.970457e+06 |
| 1443 | Guinea-Bissau | GNB | 2018 | 1.924955e+06 |
| 1444 | Guinea-Bissau | GNB | 2017 | 1.879826e+06 |
| 1445 | Guinea-Bissau | GNB | 2016 | 1.834552e+06 |
| 1446 | Guinea-Bissau | GNB | 2015 | 1.788919e+06 |
| 1447 | Guinea-Bissau | GNB | 2014 | 1.743309e+06 |
| 1448 | Guinea-Bissau | GNB | 2013 | 1.697753e+06 |
| 1449 | Guinea-Bissau | GNB | 2012 | 1.652717e+06 |
| 1450 | Guinea-Bissau | GNB | 2011 | 1.609017e+06 |
| 1451 | Guinea-Bissau | GNB | 2010 | 1.567220e+06 |
| 1452 | Guyana | GUY | 2020 | 7.972020e+05 |
| 1453 | Guyana | GUY | 2019 | 7.987530e+05 |
| 1454 | Guyana | GUY | 2018 | 7.855140e+05 |
| 1455 | Guyana | GUY | 2017 | 7.632520e+05 |
| 1456 | Guyana | GUY | 2016 | 7.590870e+05 |
| 1457 | Guyana | GUY | 2015 | 7.550310e+05 |
| 1458 | Guyana | GUY | 2014 | 7.511150e+05 |
| 1459 | Guyana | GUY | 2013 | 7.474200e+05 |
| 1460 | Guyana | GUY | 2012 | 7.439660e+05 |
| 1461 | Guyana | GUY | 2011 | 7.442300e+05 |
| 1462 | Guyana | GUY | 2010 | 7.479320e+05 |
| 1463 | Haiti | HTI | 2020 | 1.130680e+07 |
| 1464 | Haiti | HTI | 2019 | 1.116044e+07 |
| 1465 | Haiti | HTI | 2018 | 1.101242e+07 |
| 1466 | Haiti | HTI | 2017 | 1.086354e+07 |
| 1467 | Haiti | HTI | 2016 | 1.071385e+07 |
| 1468 | Haiti | HTI | 2015 | 1.056376e+07 |
| 1469 | Haiti | HTI | 2014 | 1.041274e+07 |
| 1470 | Haiti | HTI | 2013 | 1.026121e+07 |
| 1471 | Haiti | HTI | 2012 | 1.010854e+07 |
| 1472 | Haiti | HTI | 2011 | 9.954312e+06 |
| 1473 | Haiti | HTI | 2010 | 9.842880e+06 |
| 1474 | Honduras | HND | 2020 | 1.012176e+07 |
| 1475 | Honduras | HND | 2019 | 9.958829e+06 |
| 1476 | Honduras | HND | 2018 | 9.792850e+06 |
| 1477 | Honduras | HND | 2017 | 9.626842e+06 |
| 1478 | Honduras | HND | 2016 | 9.460798e+06 |
| 1479 | Honduras | HND | 2015 | 9.294505e+06 |
| 1480 | Honduras | HND | 2014 | 9.127846e+06 |
| 1481 | Honduras | HND | 2013 | 8.960657e+06 |
| 1482 | Honduras | HND | 2012 | 8.792367e+06 |
| 1483 | Honduras | HND | 2011 | 8.622504e+06 |
| 1484 | Honduras | HND | 2010 | 8.450933e+06 |
| 1485 | Hong Kong SAR, China | HKG | 2020 | 7.481000e+06 |
| 1486 | Hong Kong SAR, China | HKG | 2019 | 7.507900e+06 |
| 1487 | Hong Kong SAR, China | HKG | 2018 | 7.452600e+06 |
| 1488 | Hong Kong SAR, China | HKG | 2017 | 7.393200e+06 |
| 1489 | Hong Kong SAR, China | HKG | 2016 | 7.336600e+06 |
| 1490 | Hong Kong SAR, China | HKG | 2015 | 7.291300e+06 |
| 1491 | Hong Kong SAR, China | HKG | 2014 | 7.229500e+06 |
| 1492 | Hong Kong SAR, China | HKG | 2013 | 7.178900e+06 |
| 1493 | Hong Kong SAR, China | HKG | 2012 | 7.150100e+06 |
| 1494 | Hong Kong SAR, China | HKG | 2011 | 7.071600e+06 |
| 1495 | Hong Kong SAR, China | HKG | 2010 | 7.024200e+06 |
| 1496 | Hungary | HUN | 2020 | 9.750149e+06 |
| 1497 | Hungary | HUN | 2019 | 9.771141e+06 |
| 1498 | Hungary | HUN | 2018 | 9.775564e+06 |
| 1499 | Hungary | HUN | 2017 | 9.787966e+06 |
| 1500 | Hungary | HUN | 2016 | 9.814023e+06 |
| 1501 | Hungary | HUN | 2015 | 9.843028e+06 |
| 1502 | Hungary | HUN | 2014 | 9.866468e+06 |
| 1503 | Hungary | HUN | 2013 | 9.893082e+06 |
| 1504 | Hungary | HUN | 2012 | 9.920362e+06 |
| 1505 | Hungary | HUN | 2011 | 9.971727e+06 |
| 1506 | Hungary | HUN | 2010 | 1.000002e+07 |
| 1507 | Iceland | ISL | 2020 | 3.664630e+05 |
| 1508 | Iceland | ISL | 2019 | 3.605630e+05 |
| 1509 | Iceland | ISL | 2018 | 3.527210e+05 |
| 1510 | Iceland | ISL | 2017 | 3.434000e+05 |
| 1511 | Iceland | ISL | 2016 | 3.354390e+05 |
| 1512 | Iceland | ISL | 2015 | 3.308150e+05 |
| 1513 | Iceland | ISL | 2014 | 3.273860e+05 |
| 1514 | Iceland | ISL | 2013 | 3.237640e+05 |
| 1515 | Iceland | ISL | 2012 | 3.207160e+05 |
| 1516 | Iceland | ISL | 2011 | 3.190140e+05 |
| 1517 | Iceland | ISL | 2010 | 3.180410e+05 |
| 1518 | India | IND | 2020 | 1.396387e+09 |
| 1519 | India | IND | 2019 | 1.383112e+09 |
| 1520 | India | IND | 2018 | 1.369003e+09 |
| 1521 | India | IND | 2017 | 1.354196e+09 |
| 1522 | India | IND | 2016 | 1.338636e+09 |
| 1523 | India | IND | 2015 | 1.322867e+09 |
| 1524 | India | IND | 2014 | 1.307247e+09 |
| 1525 | India | IND | 2013 | 1.291132e+09 |
| 1526 | India | IND | 2012 | 1.274487e+09 |
| 1527 | India | IND | 2011 | 1.257621e+09 |
| 1528 | India | IND | 2010 | 1.240614e+09 |
| 1529 | Indonesia | IDN | 2020 | 2.718580e+08 |
| 1530 | Indonesia | IDN | 2019 | 2.695829e+08 |
| 1531 | Indonesia | IDN | 2018 | 2.670668e+08 |
| 1532 | Indonesia | IDN | 2017 | 2.644989e+08 |
| 1533 | Indonesia | IDN | 2016 | 2.618502e+08 |
| 1534 | Indonesia | IDN | 2015 | 2.590920e+08 |
| 1535 | Indonesia | IDN | 2014 | 2.562298e+08 |
| 1536 | Indonesia | IDN | 2013 | 2.532759e+08 |
| 1537 | Indonesia | IDN | 2012 | 2.502227e+08 |
| 1538 | Indonesia | IDN | 2011 | 2.470997e+08 |
| 1539 | Indonesia | IDN | 2010 | 2.440162e+08 |
| 1540 | Iran, Islamic Rep. | IRN | 2020 | 8.729019e+07 |
| 1541 | Iran, Islamic Rep. | IRN | 2019 | 8.656420e+07 |
| 1542 | Iran, Islamic Rep. | IRN | 2018 | 8.561756e+07 |
| 1543 | Iran, Islamic Rep. | IRN | 2017 | 8.450508e+07 |
| 1544 | Iran, Islamic Rep. | IRN | 2016 | 8.330623e+07 |
| 1545 | Iran, Islamic Rep. | IRN | 2015 | 8.179084e+07 |
| 1546 | Iran, Islamic Rep. | IRN | 2014 | 7.996167e+07 |
| 1547 | Iran, Islamic Rep. | IRN | 2013 | 7.845893e+07 |
| 1548 | Iran, Islamic Rep. | IRN | 2012 | 7.732445e+07 |
| 1549 | Iran, Islamic Rep. | IRN | 2011 | 7.634297e+07 |
| 1550 | Iran, Islamic Rep. | IRN | 2010 | 7.537386e+07 |
| 1551 | Iraq | IRQ | 2020 | 4.255698e+07 |
| 1552 | Iraq | IRQ | 2019 | 4.156352e+07 |
| 1553 | Iraq | IRQ | 2018 | 4.059070e+07 |
| 1554 | Iraq | IRQ | 2017 | 3.962116e+07 |
| 1555 | Iraq | IRQ | 2016 | 3.869794e+07 |
| 1556 | Iraq | IRQ | 2015 | 3.775781e+07 |
| 1557 | Iraq | IRQ | 2014 | 3.674649e+07 |
| 1558 | Iraq | IRQ | 2013 | 3.548180e+07 |
| 1559 | Iraq | IRQ | 2012 | 3.386445e+07 |
| 1560 | Iraq | IRQ | 2011 | 3.237806e+07 |
| 1561 | Iraq | IRQ | 2010 | 3.126488e+07 |
| 1562 | Ireland | IRL | 2020 | 4.985382e+06 |
| 1563 | Ireland | IRL | 2019 | 4.934340e+06 |
| 1564 | Ireland | IRL | 2018 | 4.867316e+06 |
| 1565 | Ireland | IRL | 2017 | 4.807388e+06 |
| 1566 | Ireland | IRL | 2016 | 4.755335e+06 |
| 1567 | Ireland | IRL | 2015 | 4.701957e+06 |
| 1568 | Ireland | IRL | 2014 | 4.657740e+06 |
| 1569 | Ireland | IRL | 2013 | 4.623816e+06 |
| 1570 | Ireland | IRL | 2012 | 4.599533e+06 |
| 1571 | Ireland | IRL | 2011 | 4.580084e+06 |
| 1572 | Ireland | IRL | 2010 | 4.560155e+06 |
| 1573 | Isle of Man | IMN | 2020 | 8.404600e+04 |
| 1574 | Isle of Man | IMN | 2019 | 8.393300e+04 |
| 1575 | Isle of Man | IMN | 2018 | 8.377500e+04 |
| 1576 | Isle of Man | IMN | 2017 | 8.358000e+04 |
| 1577 | Isle of Man | IMN | 2016 | 8.345000e+04 |
| 1578 | Isle of Man | IMN | 2015 | 8.359300e+04 |
| 1579 | Isle of Man | IMN | 2014 | 8.389600e+04 |
| 1580 | Isle of Man | IMN | 2013 | 8.414400e+04 |
| 1581 | Isle of Man | IMN | 2012 | 8.433800e+04 |
| 1582 | Isle of Man | IMN | 2011 | 8.435000e+04 |
| 1583 | Isle of Man | IMN | 2010 | 8.382800e+04 |
| 1584 | Israel | ISR | 2020 | 9.215100e+06 |
| 1585 | Israel | ISR | 2019 | 9.054000e+06 |
| 1586 | Israel | ISR | 2018 | 8.882800e+06 |
| 1587 | Israel | ISR | 2017 | 8.713300e+06 |
| 1588 | Israel | ISR | 2016 | 8.546000e+06 |
| 1589 | Israel | ISR | 2015 | 8.380100e+06 |
| 1590 | Israel | ISR | 2014 | 8.215700e+06 |
| 1591 | Israel | ISR | 2013 | 8.059500e+06 |
| 1592 | Israel | ISR | 2012 | 7.910500e+06 |
| 1593 | Israel | ISR | 2011 | 7.765800e+06 |
| 1594 | Israel | ISR | 2010 | 7.623600e+06 |
| 1595 | Italy | ITA | 2020 | 5.943885e+07 |
| 1596 | Italy | ITA | 2019 | 5.972908e+07 |
| 1597 | Italy | ITA | 2018 | 6.042176e+07 |
| 1598 | Italy | ITA | 2017 | 6.053671e+07 |
| 1599 | Italy | ITA | 2016 | 6.062750e+07 |
| 1600 | Italy | ITA | 2015 | 6.073058e+07 |
| 1601 | Italy | ITA | 2014 | 6.078914e+07 |
| 1602 | Italy | ITA | 2013 | 6.023395e+07 |
| 1603 | Italy | ITA | 2012 | 5.953972e+07 |
| 1604 | Italy | ITA | 2011 | 5.937945e+07 |
| 1605 | Italy | ITA | 2010 | 5.927742e+07 |
| 1606 | Jamaica | JAM | 2020 | 2.820436e+06 |
| 1607 | Jamaica | JAM | 2019 | 2.813773e+06 |
| 1608 | Jamaica | JAM | 2018 | 2.811835e+06 |
| 1609 | Jamaica | JAM | 2017 | 2.808376e+06 |
| 1610 | Jamaica | JAM | 2016 | 2.802695e+06 |
| 1611 | Jamaica | JAM | 2015 | 2.794445e+06 |
| 1612 | Jamaica | JAM | 2014 | 2.784543e+06 |
| 1613 | Jamaica | JAM | 2013 | 2.773129e+06 |
| 1614 | Jamaica | JAM | 2012 | 2.759817e+06 |
| 1615 | Jamaica | JAM | 2011 | 2.746169e+06 |
| 1616 | Jamaica | JAM | 2010 | 2.733896e+06 |
| 1617 | Japan | JPN | 2020 | 1.262610e+08 |
| 1618 | Japan | JPN | 2019 | 1.266330e+08 |
| 1619 | Japan | JPN | 2018 | 1.268110e+08 |
| 1620 | Japan | JPN | 2017 | 1.269720e+08 |
| 1621 | Japan | JPN | 2016 | 1.270760e+08 |
| 1622 | Japan | JPN | 2015 | 1.271410e+08 |
| 1623 | Japan | JPN | 2014 | 1.272760e+08 |
| 1624 | Japan | JPN | 2013 | 1.274450e+08 |
| 1625 | Japan | JPN | 2012 | 1.276290e+08 |
| 1626 | Japan | JPN | 2011 | 1.278330e+08 |
| 1627 | Japan | JPN | 2010 | 1.280700e+08 |
| 1628 | Jordan | JOR | 2020 | 1.092872e+07 |
| 1629 | Jordan | JOR | 2019 | 1.069868e+07 |
| 1630 | Jordan | JOR | 2018 | 1.045986e+07 |
| 1631 | Jordan | JOR | 2017 | 1.021538e+07 |
| 1632 | Jordan | JOR | 2016 | 9.964656e+06 |
| 1633 | Jordan | JOR | 2015 | 9.494246e+06 |
| 1634 | Jordan | JOR | 2014 | 8.658026e+06 |
| 1635 | Jordan | JOR | 2013 | 7.694814e+06 |
| 1636 | Jordan | JOR | 2012 | 7.211863e+06 |
| 1637 | Jordan | JOR | 2011 | 7.109980e+06 |
| 1638 | Jordan | JOR | 2010 | 6.931258e+06 |
| 1639 | Kazakhstan | KAZ | 2020 | 1.875567e+07 |
| 1640 | Kazakhstan | KAZ | 2019 | 1.851367e+07 |
| 1641 | Kazakhstan | KAZ | 2018 | 1.827645e+07 |
| 1642 | Kazakhstan | KAZ | 2017 | 1.803778e+07 |
| 1643 | Kazakhstan | KAZ | 2016 | 1.779406e+07 |
| 1644 | Kazakhstan | KAZ | 2015 | 1.754281e+07 |
| 1645 | Kazakhstan | KAZ | 2014 | 1.728828e+07 |
| 1646 | Kazakhstan | KAZ | 2013 | 1.703555e+07 |
| 1647 | Kazakhstan | KAZ | 2012 | 1.679209e+07 |
| 1648 | Kazakhstan | KAZ | 2011 | 1.655720e+07 |
| 1649 | Kazakhstan | KAZ | 2010 | 1.632187e+07 |
| 1650 | Kenya | KEN | 2020 | 5.198578e+07 |
| 1651 | Kenya | KEN | 2019 | 5.095145e+07 |
| 1652 | Kenya | KEN | 2018 | 4.995330e+07 |
| 1653 | Kenya | KEN | 2017 | 4.894814e+07 |
| 1654 | Kenya | KEN | 2016 | 4.789467e+07 |
| 1655 | Kenya | KEN | 2015 | 4.685149e+07 |
| 1656 | Kenya | KEN | 2014 | 4.583186e+07 |
| 1657 | Kenya | KEN | 2013 | 4.479237e+07 |
| 1658 | Kenya | KEN | 2012 | 4.372581e+07 |
| 1659 | Kenya | KEN | 2011 | 4.263514e+07 |
| 1660 | Kenya | KEN | 2010 | 4.151790e+07 |
| 1661 | Kiribati | KIR | 2020 | 1.264630e+05 |
| 1662 | Kiribati | KIR | 2019 | 1.242410e+05 |
| 1663 | Kiribati | KIR | 2018 | 1.222610e+05 |
| 1664 | Kiribati | KIR | 2017 | 1.203620e+05 |
| 1665 | Kiribati | KIR | 2016 | 1.185130e+05 |
| 1666 | Kiribati | KIR | 2015 | 1.167070e+05 |
| 1667 | Kiribati | KIR | 2014 | 1.149850e+05 |
| 1668 | Kiribati | KIR | 2013 | 1.133110e+05 |
| 1669 | Kiribati | KIR | 2012 | 1.116180e+05 |
| 1670 | Kiribati | KIR | 2011 | 1.098710e+05 |
| 1671 | Kiribati | KIR | 2010 | 1.079950e+05 |
| 1672 | Korea, Dem. People's Rep. | PRK | 2020 | 2.586747e+07 |
| 1673 | Korea, Dem. People's Rep. | PRK | 2019 | 2.575544e+07 |
| 1674 | Korea, Dem. People's Rep. | PRK | 2018 | 2.563815e+07 |
| 1675 | Korea, Dem. People's Rep. | PRK | 2017 | 2.551632e+07 |
| 1676 | Korea, Dem. People's Rep. | PRK | 2016 | 2.538961e+07 |
| 1677 | Korea, Dem. People's Rep. | PRK | 2015 | 2.525802e+07 |
| 1678 | Korea, Dem. People's Rep. | PRK | 2014 | 2.512613e+07 |
| 1679 | Korea, Dem. People's Rep. | PRK | 2013 | 2.500182e+07 |
| 1680 | Korea, Dem. People's Rep. | PRK | 2012 | 2.488777e+07 |
| 1681 | Korea, Dem. People's Rep. | PRK | 2011 | 2.478379e+07 |
| 1682 | Korea, Dem. People's Rep. | PRK | 2010 | 2.468644e+07 |
| 1683 | Korea, Rep. | KOR | 2020 | 5.183624e+07 |
| 1684 | Korea, Rep. | KOR | 2019 | 5.176482e+07 |
| 1685 | Korea, Rep. | KOR | 2018 | 5.158506e+07 |
| 1686 | Korea, Rep. | KOR | 2017 | 5.136191e+07 |
| 1687 | Korea, Rep. | KOR | 2016 | 5.121780e+07 |
| 1688 | Korea, Rep. | KOR | 2015 | 5.101495e+07 |
| 1689 | Korea, Rep. | KOR | 2014 | 5.074666e+07 |
| 1690 | Korea, Rep. | KOR | 2013 | 5.042889e+07 |
| 1691 | Korea, Rep. | KOR | 2012 | 5.019985e+07 |
| 1692 | Korea, Rep. | KOR | 2011 | 4.993664e+07 |
| 1693 | Korea, Rep. | KOR | 2010 | 4.955411e+07 |
| 1694 | Kosovo | XKX | 2020 | 1.790133e+06 |
| 1695 | Kosovo | XKX | 2019 | 1.788878e+06 |
| 1696 | Kosovo | XKX | 2018 | 1.797085e+06 |
| 1697 | Kosovo | XKX | 2017 | 1.791003e+06 |
| 1698 | Kosovo | XKX | 2016 | 1.777557e+06 |
| 1699 | Kosovo | XKX | 2015 | 1.788196e+06 |
| 1700 | Kosovo | XKX | 2014 | 1.812771e+06 |
| 1701 | Kosovo | XKX | 2013 | 1.818117e+06 |
| 1702 | Kosovo | XKX | 2012 | 1.807106e+06 |
| 1703 | Kosovo | XKX | 2011 | 1.791000e+06 |
| 1704 | Kosovo | XKX | 2010 | 1.775680e+06 |
| 1705 | Kuwait | KWT | 2020 | 4.360444e+06 |
| 1706 | Kuwait | KWT | 2019 | 4.441100e+06 |
| 1707 | Kuwait | KWT | 2018 | 4.317185e+06 |
| 1708 | Kuwait | KWT | 2017 | 4.124904e+06 |
| 1709 | Kuwait | KWT | 2016 | 4.048085e+06 |
| 1710 | Kuwait | KWT | 2015 | 3.908743e+06 |
| 1711 | Kuwait | KWT | 2014 | 3.761584e+06 |
| 1712 | Kuwait | KWT | 2013 | 3.646518e+06 |
| 1713 | Kuwait | KWT | 2012 | 3.394663e+06 |
| 1714 | Kuwait | KWT | 2011 | 3.143825e+06 |
| 1715 | Kuwait | KWT | 2010 | 2.943356e+06 |
| 1716 | Kyrgyz Republic | KGZ | 2020 | 6.579900e+06 |
| 1717 | Kyrgyz Republic | KGZ | 2019 | 6.456200e+06 |
| 1718 | Kyrgyz Republic | KGZ | 2018 | 6.322800e+06 |
| 1719 | Kyrgyz Republic | KGZ | 2017 | 6.198200e+06 |
| 1720 | Kyrgyz Republic | KGZ | 2016 | 6.079500e+06 |
| 1721 | Kyrgyz Republic | KGZ | 2015 | 5.956900e+06 |
| 1722 | Kyrgyz Republic | KGZ | 2014 | 5.835500e+06 |
| 1723 | Kyrgyz Republic | KGZ | 2013 | 5.719600e+06 |
| 1724 | Kyrgyz Republic | KGZ | 2012 | 5.607200e+06 |
| 1725 | Kyrgyz Republic | KGZ | 2011 | 5.514600e+06 |
| 1726 | Kyrgyz Republic | KGZ | 2010 | 5.447900e+06 |
| 1727 | Lao PDR | LAO | 2020 | 7.319399e+06 |
| 1728 | Lao PDR | LAO | 2019 | 7.212053e+06 |
| 1729 | Lao PDR | LAO | 2018 | 7.105006e+06 |
| 1730 | Lao PDR | LAO | 2017 | 6.997917e+06 |
| 1731 | Lao PDR | LAO | 2016 | 6.891363e+06 |
| 1732 | Lao PDR | LAO | 2015 | 6.787419e+06 |
| 1733 | Lao PDR | LAO | 2014 | 6.691454e+06 |
| 1734 | Lao PDR | LAO | 2013 | 6.600742e+06 |
| 1735 | Lao PDR | LAO | 2012 | 6.508803e+06 |
| 1736 | Lao PDR | LAO | 2011 | 6.416327e+06 |
| 1737 | Lao PDR | LAO | 2010 | 6.323418e+06 |
| 1738 | Latvia | LVA | 2020 | 1.900449e+06 |
| 1739 | Latvia | LVA | 2019 | 1.913822e+06 |
| 1740 | Latvia | LVA | 2018 | 1.927174e+06 |
| 1741 | Latvia | LVA | 2017 | 1.942248e+06 |
| 1742 | Latvia | LVA | 2016 | 1.959537e+06 |
| 1743 | Latvia | LVA | 2015 | 1.977527e+06 |
| 1744 | Latvia | LVA | 2014 | 1.993782e+06 |
| 1745 | Latvia | LVA | 2013 | 2.012647e+06 |
| 1746 | Latvia | LVA | 2012 | 2.034319e+06 |
| 1747 | Latvia | LVA | 2011 | 2.059709e+06 |
| 1748 | Latvia | LVA | 2010 | 2.097555e+06 |
| 1749 | Lebanon | LBN | 2020 | 5.662923e+06 |
| 1750 | Lebanon | LBN | 2019 | 5.781907e+06 |
| 1751 | Lebanon | LBN | 2018 | 5.950839e+06 |
| 1752 | Lebanon | LBN | 2017 | 6.109252e+06 |
| 1753 | Lebanon | LBN | 2016 | 6.258619e+06 |
| 1754 | Lebanon | LBN | 2015 | 6.398940e+06 |
| 1755 | Lebanon | LBN | 2014 | 6.274342e+06 |
| 1756 | Lebanon | LBN | 2013 | 5.678851e+06 |
| 1757 | Lebanon | LBN | 2012 | 5.178337e+06 |
| 1758 | Lebanon | LBN | 2011 | 5.045056e+06 |
| 1759 | Lebanon | LBN | 2010 | 4.995800e+06 |
| 1760 | Lesotho | LSO | 2020 | 2.254100e+06 |
| 1761 | Lesotho | LSO | 2019 | 2.225702e+06 |
| 1762 | Lesotho | LSO | 2018 | 2.198017e+06 |
| 1763 | Lesotho | LSO | 2017 | 2.170617e+06 |
| 1764 | Lesotho | LSO | 2016 | 2.143872e+06 |
| 1765 | Lesotho | LSO | 2015 | 2.118521e+06 |
| 1766 | Lesotho | LSO | 2014 | 2.095242e+06 |
| 1767 | Lesotho | LSO | 2013 | 2.073939e+06 |
| 1768 | Lesotho | LSO | 2012 | 2.054718e+06 |
| 1769 | Lesotho | LSO | 2011 | 2.037677e+06 |
| 1770 | Lesotho | LSO | 2010 | 2.022747e+06 |
| 1771 | Liberia | LBR | 2020 | 5.087584e+06 |
| 1772 | Liberia | LBR | 2019 | 4.985289e+06 |
| 1773 | Liberia | LBR | 2018 | 4.889391e+06 |
| 1774 | Liberia | LBR | 2017 | 4.796631e+06 |
| 1775 | Liberia | LBR | 2016 | 4.706097e+06 |
| 1776 | Liberia | LBR | 2015 | 4.612329e+06 |
| 1777 | Liberia | LBR | 2014 | 4.519398e+06 |
| 1778 | Liberia | LBR | 2013 | 4.427313e+06 |
| 1779 | Liberia | LBR | 2012 | 4.331740e+06 |
| 1780 | Liberia | LBR | 2011 | 4.181150e+06 |
| 1781 | Liberia | LBR | 2010 | 4.019956e+06 |
| 1782 | Libya | LBY | 2020 | 6.653942e+06 |
| 1783 | Libya | LBY | 2019 | 6.569088e+06 |
| 1784 | Libya | LBY | 2018 | 6.477793e+06 |
| 1785 | Libya | LBY | 2017 | 6.378261e+06 |
| 1786 | Libya | LBY | 2016 | 6.282196e+06 |
| 1787 | Libya | LBY | 2015 | 6.192235e+06 |
| 1788 | Libya | LBY | 2014 | 6.097764e+06 |
| 1789 | Libya | LBY | 2013 | 5.985221e+06 |
| 1790 | Libya | LBY | 2012 | 5.869870e+06 |
| 1791 | Libya | LBY | 2011 | 6.188132e+06 |
| 1792 | Libya | LBY | 2010 | 6.491988e+06 |
| 1793 | Liechtenstein | LIE | 2020 | 3.875600e+04 |
| 1794 | Liechtenstein | LIE | 2019 | 3.848200e+04 |
| 1795 | Liechtenstein | LIE | 2018 | 3.818100e+04 |
| 1796 | Liechtenstein | LIE | 2017 | 3.788900e+04 |
| 1797 | Liechtenstein | LIE | 2016 | 3.760900e+04 |
| 1798 | Liechtenstein | LIE | 2015 | 3.735500e+04 |
| 1799 | Liechtenstein | LIE | 2014 | 3.709600e+04 |
| 1800 | Liechtenstein | LIE | 2013 | 3.680600e+04 |
| 1801 | Liechtenstein | LIE | 2012 | 3.650500e+04 |
| 1802 | Liechtenstein | LIE | 2011 | 3.618900e+04 |
| 1803 | Liechtenstein | LIE | 2010 | 3.592600e+04 |
| 1804 | Lithuania | LTU | 2020 | 2.794885e+06 |
| 1805 | Lithuania | LTU | 2019 | 2.794137e+06 |
| 1806 | Lithuania | LTU | 2018 | 2.801543e+06 |
| 1807 | Lithuania | LTU | 2017 | 2.828403e+06 |
| 1808 | Lithuania | LTU | 2016 | 2.868231e+06 |
| 1809 | Lithuania | LTU | 2015 | 2.904910e+06 |
| 1810 | Lithuania | LTU | 2014 | 2.932367e+06 |
| 1811 | Lithuania | LTU | 2013 | 2.957689e+06 |
| 1812 | Lithuania | LTU | 2012 | 2.987773e+06 |
| 1813 | Lithuania | LTU | 2011 | 3.028115e+06 |
| 1814 | Lithuania | LTU | 2010 | 3.097282e+06 |
| 1815 | Luxembourg | LUX | 2020 | 6.304190e+05 |
| 1816 | Luxembourg | LUX | 2019 | 6.200010e+05 |
| 1817 | Luxembourg | LUX | 2018 | 6.079500e+05 |
| 1818 | Luxembourg | LUX | 2017 | 5.963360e+05 |
| 1819 | Luxembourg | LUX | 2016 | 5.820140e+05 |
| 1820 | Luxembourg | LUX | 2015 | 5.696040e+05 |
| 1821 | Luxembourg | LUX | 2014 | 5.563190e+05 |
| 1822 | Luxembourg | LUX | 2013 | 5.433600e+05 |
| 1823 | Luxembourg | LUX | 2012 | 5.309460e+05 |
| 1824 | Luxembourg | LUX | 2011 | 5.183470e+05 |
| 1825 | Luxembourg | LUX | 2010 | 5.069530e+05 |
| 1826 | Macao SAR, China | MAC | 2020 | 6.762830e+05 |
| 1827 | Macao SAR, China | MAC | 2019 | 6.636530e+05 |
| 1828 | Macao SAR, China | MAC | 2018 | 6.509910e+05 |
| 1829 | Macao SAR, China | MAC | 2017 | 6.386090e+05 |
| 1830 | Macao SAR, China | MAC | 2016 | 6.266880e+05 |
| 1831 | Macao SAR, China | MAC | 2015 | 6.152390e+05 |
| 1832 | Macao SAR, China | MAC | 2014 | 6.041670e+05 |
| 1833 | Macao SAR, China | MAC | 2013 | 5.933740e+05 |
| 1834 | Macao SAR, China | MAC | 2012 | 5.827660e+05 |
| 1835 | Macao SAR, China | MAC | 2011 | 5.710030e+05 |
| 1836 | Macao SAR, China | MAC | 2010 | 5.572970e+05 |
| 1837 | Madagascar | MDG | 2020 | 2.822518e+07 |
| 1838 | Madagascar | MDG | 2019 | 2.753313e+07 |
| 1839 | Madagascar | MDG | 2018 | 2.684654e+07 |
| 1840 | Madagascar | MDG | 2017 | 2.616954e+07 |
| 1841 | Madagascar | MDG | 2016 | 2.550194e+07 |
| 1842 | Madagascar | MDG | 2015 | 2.485091e+07 |
| 1843 | Madagascar | MDG | 2014 | 2.421598e+07 |
| 1844 | Madagascar | MDG | 2013 | 2.358807e+07 |
| 1845 | Madagascar | MDG | 2012 | 2.296624e+07 |
| 1846 | Madagascar | MDG | 2011 | 2.234816e+07 |
| 1847 | Madagascar | MDG | 2010 | 2.173105e+07 |
| 1848 | Malawi | MWI | 2020 | 1.937706e+07 |
| 1849 | Malawi | MWI | 2019 | 1.886734e+07 |
| 1850 | Malawi | MWI | 2018 | 1.836788e+07 |
| 1851 | Malawi | MWI | 2017 | 1.788117e+07 |
| 1852 | Malawi | MWI | 2016 | 1.740562e+07 |
| 1853 | Malawi | MWI | 2015 | 1.693894e+07 |
| 1854 | Malawi | MWI | 2014 | 1.647797e+07 |
| 1855 | Malawi | MWI | 2013 | 1.602478e+07 |
| 1856 | Malawi | MWI | 2012 | 1.558125e+07 |
| 1857 | Malawi | MWI | 2011 | 1.514609e+07 |
| 1858 | Malawi | MWI | 2010 | 1.471842e+07 |
| 1859 | Malaysia | MYS | 2020 | 3.319999e+07 |
| 1860 | Malaysia | MYS | 2019 | 3.280402e+07 |
| 1861 | Malaysia | MYS | 2018 | 3.239927e+07 |
| 1862 | Malaysia | MYS | 2017 | 3.197581e+07 |
| 1863 | Malaysia | MYS | 2016 | 3.152642e+07 |
| 1864 | Malaysia | MYS | 2015 | 3.106883e+07 |
| 1865 | Malaysia | MYS | 2014 | 3.060646e+07 |
| 1866 | Malaysia | MYS | 2013 | 3.013481e+07 |
| 1867 | Malaysia | MYS | 2012 | 2.966021e+07 |
| 1868 | Malaysia | MYS | 2011 | 2.918413e+07 |
| 1869 | Malaysia | MYS | 2010 | 2.871773e+07 |
| 1870 | Maldives | MDV | 2020 | 5.144380e+05 |
| 1871 | Maldives | MDV | 2019 | 5.045080e+05 |
| 1872 | Maldives | MDV | 2018 | 4.897580e+05 |
| 1873 | Maldives | MDV | 2017 | 4.724420e+05 |
| 1874 | Maldives | MDV | 2016 | 4.542520e+05 |
| 1875 | Maldives | MDV | 2015 | 4.355820e+05 |
| 1876 | Maldives | MDV | 2014 | 4.167380e+05 |
| 1877 | Maldives | MDV | 2013 | 4.007280e+05 |
| 1878 | Maldives | MDV | 2012 | 3.875390e+05 |
| 1879 | Maldives | MDV | 2011 | 3.744400e+05 |
| 1880 | Maldives | MDV | 2010 | 3.615750e+05 |
| 1881 | Mali | MLI | 2020 | 2.122404e+07 |
| 1882 | Mali | MLI | 2019 | 2.056742e+07 |
| 1883 | Mali | MLI | 2018 | 1.993430e+07 |
| 1884 | Mali | MLI | 2017 | 1.931136e+07 |
| 1885 | Mali | MLI | 2016 | 1.870011e+07 |
| 1886 | Mali | MLI | 2015 | 1.811291e+07 |
| 1887 | Mali | MLI | 2014 | 1.755181e+07 |
| 1888 | Mali | MLI | 2013 | 1.700403e+07 |
| 1889 | Mali | MLI | 2012 | 1.651469e+07 |
| 1890 | Mali | MLI | 2011 | 1.603973e+07 |
| 1891 | Mali | MLI | 2010 | 1.552918e+07 |
| 1892 | Malta | MLT | 2020 | 5.153320e+05 |
| 1893 | Malta | MLT | 2019 | 5.040620e+05 |
| 1894 | Malta | MLT | 2018 | 4.846300e+05 |
| 1895 | Malta | MLT | 2017 | 4.679990e+05 |
| 1896 | Malta | MLT | 2016 | 4.553560e+05 |
| 1897 | Malta | MLT | 2015 | 4.450530e+05 |
| 1898 | Malta | MLT | 2014 | 4.345580e+05 |
| 1899 | Malta | MLT | 2013 | 4.259670e+05 |
| 1900 | Malta | MLT | 2012 | 4.200280e+05 |
| 1901 | Malta | MLT | 2011 | 4.162680e+05 |
| 1902 | Malta | MLT | 2010 | 4.145080e+05 |
| 1903 | Marshall Islands | MHL | 2020 | 4.341300e+04 |
| 1904 | Marshall Islands | MHL | 2019 | 4.472800e+04 |
| 1905 | Marshall Islands | MHL | 2018 | 4.598900e+04 |
| 1906 | Marshall Islands | MHL | 2017 | 4.718700e+04 |
| 1907 | Marshall Islands | MHL | 2016 | 4.832900e+04 |
| 1908 | Marshall Islands | MHL | 2015 | 4.941000e+04 |
| 1909 | Marshall Islands | MHL | 2014 | 5.041900e+04 |
| 1910 | Marshall Islands | MHL | 2013 | 5.135200e+04 |
| 1911 | Marshall Islands | MHL | 2012 | 5.220300e+04 |
| 1912 | Marshall Islands | MHL | 2011 | 5.297100e+04 |
| 1913 | Marshall Islands | MHL | 2010 | 5.341600e+04 |
| 1914 | Mauritania | MRT | 2020 | 4.498604e+06 |
| 1915 | Mauritania | MRT | 2019 | 4.383849e+06 |
| 1916 | Mauritania | MRT | 2018 | 4.270712e+06 |
| 1917 | Mauritania | MRT | 2017 | 4.160015e+06 |
| 1918 | Mauritania | MRT | 2016 | 4.051890e+06 |
| 1919 | Mauritania | MRT | 2015 | 3.946220e+06 |
| 1920 | Mauritania | MRT | 2014 | 3.843174e+06 |
| 1921 | Mauritania | MRT | 2013 | 3.742959e+06 |
| 1922 | Mauritania | MRT | 2012 | 3.636113e+06 |
| 1923 | Mauritania | MRT | 2011 | 3.524249e+06 |
| 1924 | Mauritania | MRT | 2010 | 3.419461e+06 |
| 1925 | Mauritius | MUS | 2020 | 1.266014e+06 |
| 1926 | Mauritius | MUS | 2019 | 1.265985e+06 |
| 1927 | Mauritius | MUS | 2018 | 1.265577e+06 |
| 1928 | Mauritius | MUS | 2017 | 1.264887e+06 |
| 1929 | Mauritius | MUS | 2016 | 1.263747e+06 |
| 1930 | Mauritius | MUS | 2015 | 1.262879e+06 |
| 1931 | Mauritius | MUS | 2014 | 1.261208e+06 |
| 1932 | Mauritius | MUS | 2013 | 1.258927e+06 |
| 1933 | Mauritius | MUS | 2012 | 1.255882e+06 |
| 1934 | Mauritius | MUS | 2011 | 1.252404e+06 |
| 1935 | Mauritius | MUS | 2010 | 1.250400e+06 |
| 1936 | Mexico | MEX | 2020 | 1.259983e+08 |
| 1937 | Mexico | MEX | 2019 | 1.250853e+08 |
| 1938 | Mexico | MEX | 2018 | 1.240139e+08 |
| 1939 | Mexico | MEX | 2017 | 1.228393e+08 |
| 1940 | Mexico | MEX | 2016 | 1.215192e+08 |
| 1941 | Mexico | MEX | 2015 | 1.201499e+08 |
| 1942 | Mexico | MEX | 2014 | 1.187559e+08 |
| 1943 | Mexico | MEX | 2013 | 1.172907e+08 |
| 1944 | Mexico | MEX | 2012 | 1.157559e+08 |
| 1945 | Mexico | MEX | 2011 | 1.141505e+08 |
| 1946 | Mexico | MEX | 2010 | 1.125324e+08 |
| 1947 | Micronesia, Fed. Sts. | FSM | 2020 | 1.121060e+05 |
| 1948 | Micronesia, Fed. Sts. | FSM | 2019 | 1.113790e+05 |
| 1949 | Micronesia, Fed. Sts. | FSM | 2018 | 1.109290e+05 |
| 1950 | Micronesia, Fed. Sts. | FSM | 2017 | 1.104300e+05 |
| 1951 | Micronesia, Fed. Sts. | FSM | 2016 | 1.099250e+05 |
| 1952 | Micronesia, Fed. Sts. | FSM | 2015 | 1.094620e+05 |
| 1953 | Micronesia, Fed. Sts. | FSM | 2014 | 1.090240e+05 |
| 1954 | Micronesia, Fed. Sts. | FSM | 2013 | 1.086090e+05 |
| 1955 | Micronesia, Fed. Sts. | FSM | 2012 | 1.082320e+05 |
| 1956 | Micronesia, Fed. Sts. | FSM | 2011 | 1.078870e+05 |
| 1957 | Micronesia, Fed. Sts. | FSM | 2010 | 1.075880e+05 |
| 1958 | Moldova | MDA | 2020 | 2.635130e+06 |
| 1959 | Moldova | MDA | 2019 | 2.664224e+06 |
| 1960 | Moldova | MDA | 2018 | 2.707203e+06 |
| 1961 | Moldova | MDA | 2017 | 2.755189e+06 |
| 1962 | Moldova | MDA | 2016 | 2.803186e+06 |
| 1963 | Moldova | MDA | 2015 | 2.835978e+06 |
| 1964 | Moldova | MDA | 2014 | 2.857815e+06 |
| 1965 | Moldova | MDA | 2013 | 2.859558e+06 |
| 1966 | Moldova | MDA | 2012 | 2.860324e+06 |
| 1967 | Moldova | MDA | 2011 | 2.860699e+06 |
| 1968 | Moldova | MDA | 2010 | 2.862354e+06 |
| 1969 | Monaco | MCO | 2020 | 3.692200e+04 |
| 1970 | Monaco | MCO | 2019 | 3.703400e+04 |
| 1971 | Monaco | MCO | 2018 | 3.702900e+04 |
| 1972 | Monaco | MCO | 2017 | 3.704400e+04 |
| 1973 | Monaco | MCO | 2016 | 3.707100e+04 |
| 1974 | Monaco | MCO | 2015 | 3.676000e+04 |
| 1975 | Monaco | MCO | 2014 | 3.611000e+04 |
| 1976 | Monaco | MCO | 2013 | 3.542500e+04 |
| 1977 | Monaco | MCO | 2012 | 3.470000e+04 |
| 1978 | Monaco | MCO | 2011 | 3.394500e+04 |
| 1979 | Monaco | MCO | 2010 | 3.317800e+04 |
| 1980 | Mongolia | MNG | 2020 | 3.294335e+06 |
| 1981 | Mongolia | MNG | 2019 | 3.232430e+06 |
| 1982 | Mongolia | MNG | 2018 | 3.163991e+06 |
| 1983 | Mongolia | MNG | 2017 | 3.096030e+06 |
| 1984 | Mongolia | MNG | 2016 | 3.029555e+06 |
| 1985 | Mongolia | MNG | 2015 | 2.964749e+06 |
| 1986 | Mongolia | MNG | 2014 | 2.902823e+06 |
| 1987 | Mongolia | MNG | 2013 | 2.845153e+06 |
| 1988 | Mongolia | MNG | 2012 | 2.792349e+06 |
| 1989 | Mongolia | MNG | 2011 | 2.743938e+06 |
| 1990 | Mongolia | MNG | 2010 | 2.702520e+06 |
| 1991 | Montenegro | MNE | 2020 | 6.213060e+05 |
| 1992 | Montenegro | MNE | 2019 | 6.220280e+05 |
| 1993 | Montenegro | MNE | 2018 | 6.222270e+05 |
| 1994 | Montenegro | MNE | 2017 | 6.223730e+05 |
| 1995 | Montenegro | MNE | 2016 | 6.223030e+05 |
| 1996 | Montenegro | MNE | 2015 | 6.221590e+05 |
| 1997 | Montenegro | MNE | 2014 | 6.218100e+05 |
| 1998 | Montenegro | MNE | 2013 | 6.212070e+05 |
| 1999 | Montenegro | MNE | 2012 | 6.206010e+05 |
| 2000 | Montenegro | MNE | 2011 | 6.200790e+05 |
| 2001 | Montenegro | MNE | 2010 | 6.194280e+05 |
| 2002 | Morocco | MAR | 2020 | 3.668877e+07 |
| 2003 | Morocco | MAR | 2019 | 3.630441e+07 |
| 2004 | Morocco | MAR | 2018 | 3.592751e+07 |
| 2005 | Morocco | MAR | 2017 | 3.552812e+07 |
| 2006 | Morocco | MAR | 2016 | 3.510726e+07 |
| 2007 | Morocco | MAR | 2015 | 3.468046e+07 |
| 2008 | Morocco | MAR | 2014 | 3.424860e+07 |
| 2009 | Morocco | MAR | 2013 | 3.380353e+07 |
| 2010 | Morocco | MAR | 2012 | 3.335217e+07 |
| 2011 | Morocco | MAR | 2011 | 3.290370e+07 |
| 2012 | Morocco | MAR | 2010 | 3.246486e+07 |
| 2013 | Mozambique | MOZ | 2020 | 3.117824e+07 |
| 2014 | Mozambique | MOZ | 2019 | 3.028560e+07 |
| 2015 | Mozambique | MOZ | 2018 | 2.942388e+07 |
| 2016 | Mozambique | MOZ | 2017 | 2.856944e+07 |
| 2017 | Mozambique | MOZ | 2016 | 2.769649e+07 |
| 2018 | Mozambique | MOZ | 2015 | 2.684325e+07 |
| 2019 | Mozambique | MOZ | 2014 | 2.603870e+07 |
| 2020 | Mozambique | MOZ | 2013 | 2.525173e+07 |
| 2021 | Mozambique | MOZ | 2012 | 2.448761e+07 |
| 2022 | Mozambique | MOZ | 2011 | 2.376042e+07 |
| 2023 | Mozambique | MOZ | 2010 | 2.307372e+07 |
| 2024 | Myanmar | MMR | 2020 | 5.342320e+07 |
| 2025 | Myanmar | MMR | 2019 | 5.304021e+07 |
| 2026 | Myanmar | MMR | 2018 | 5.266601e+07 |
| 2027 | Myanmar | MMR | 2017 | 5.228834e+07 |
| 2028 | Myanmar | MMR | 2016 | 5.189235e+07 |
| 2029 | Myanmar | MMR | 2015 | 5.148395e+07 |
| 2030 | Myanmar | MMR | 2014 | 5.107244e+07 |
| 2031 | Myanmar | MMR | 2013 | 5.064833e+07 |
| 2032 | Myanmar | MMR | 2012 | 5.021818e+07 |
| 2033 | Myanmar | MMR | 2011 | 4.979452e+07 |
| 2034 | Myanmar | MMR | 2010 | 4.939099e+07 |
| 2035 | Namibia | NAM | 2020 | 2.489098e+06 |
| 2036 | Namibia | NAM | 2019 | 2.446644e+06 |
| 2037 | Namibia | NAM | 2018 | 2.405680e+06 |
| 2038 | Namibia | NAM | 2017 | 2.364534e+06 |
| 2039 | Namibia | NAM | 2016 | 2.323352e+06 |
| 2040 | Namibia | NAM | 2015 | 2.282704e+06 |
| 2041 | Namibia | NAM | 2014 | 2.243001e+06 |
| 2042 | Namibia | NAM | 2013 | 2.204510e+06 |
| 2043 | Namibia | NAM | 2012 | 2.167470e+06 |
| 2044 | Namibia | NAM | 2011 | 2.132340e+06 |
| 2045 | Namibia | NAM | 2010 | 2.099271e+06 |
| 2046 | Nauru | NRU | 2020 | 1.231500e+04 |
| 2047 | Nauru | NRU | 2019 | 1.213200e+04 |
| 2048 | Nauru | NRU | 2018 | 1.192400e+04 |
| 2049 | Nauru | NRU | 2017 | 1.168200e+04 |
| 2050 | Nauru | NRU | 2016 | 1.143700e+04 |
| 2051 | Nauru | NRU | 2015 | 1.118500e+04 |
| 2052 | Nauru | NRU | 2014 | 1.094000e+04 |
| 2053 | Nauru | NRU | 2013 | 1.069400e+04 |
| 2054 | Nauru | NRU | 2012 | 1.044400e+04 |
| 2055 | Nauru | NRU | 2011 | 1.028300e+04 |
| 2056 | Nauru | NRU | 2010 | 1.024100e+04 |
| 2057 | Nepal | NPL | 2020 | 2.934863e+07 |
| 2058 | Nepal | NPL | 2019 | 2.883250e+07 |
| 2059 | Nepal | NPL | 2018 | 2.850671e+07 |
| 2060 | Nepal | NPL | 2017 | 2.818343e+07 |
| 2061 | Nepal | NPL | 2016 | 2.786119e+07 |
| 2062 | Nepal | NPL | 2015 | 2.761032e+07 |
| 2063 | Nepal | NPL | 2014 | 2.746211e+07 |
| 2064 | Nepal | NPL | 2013 | 2.738156e+07 |
| 2065 | Nepal | NPL | 2012 | 2.733069e+07 |
| 2066 | Nepal | NPL | 2011 | 2.726640e+07 |
| 2067 | Nepal | NPL | 2010 | 2.716157e+07 |
| 2068 | Netherlands | NLD | 2020 | 1.744150e+07 |
| 2069 | Netherlands | NLD | 2019 | 1.734487e+07 |
| 2070 | Netherlands | NLD | 2018 | 1.723162e+07 |
| 2071 | Netherlands | NLD | 2017 | 1.713130e+07 |
| 2072 | Netherlands | NLD | 2016 | 1.703031e+07 |
| 2073 | Netherlands | NLD | 2015 | 1.693992e+07 |
| 2074 | Netherlands | NLD | 2014 | 1.686501e+07 |
| 2075 | Netherlands | NLD | 2013 | 1.680443e+07 |
| 2076 | Netherlands | NLD | 2012 | 1.675496e+07 |
| 2077 | Netherlands | NLD | 2011 | 1.669307e+07 |
| 2078 | Netherlands | NLD | 2010 | 1.661539e+07 |
| 2079 | New Caledonia | NCL | 2020 | 2.710800e+05 |
| 2080 | New Caledonia | NCL | 2019 | 2.712400e+05 |
| 2081 | New Caledonia | NCL | 2018 | 2.711700e+05 |
| 2082 | New Caledonia | NCL | 2017 | 2.708100e+05 |
| 2083 | New Caledonia | NCL | 2016 | 2.702200e+05 |
| 2084 | New Caledonia | NCL | 2015 | 2.694600e+05 |
| 2085 | New Caledonia | NCL | 2014 | 2.680500e+05 |
| 2086 | New Caledonia | NCL | 2013 | 2.636500e+05 |
| 2087 | New Caledonia | NCL | 2012 | 2.590000e+05 |
| 2088 | New Caledonia | NCL | 2011 | 2.543500e+05 |
| 2089 | New Caledonia | NCL | 2010 | 2.497500e+05 |
| 2090 | New Zealand | NZL | 2020 | 5.090200e+06 |
| 2091 | New Zealand | NZL | 2019 | 4.979200e+06 |
| 2092 | New Zealand | NZL | 2018 | 4.900600e+06 |
| 2093 | New Zealand | NZL | 2017 | 4.813600e+06 |
| 2094 | New Zealand | NZL | 2016 | 4.714100e+06 |
| 2095 | New Zealand | NZL | 2015 | 4.609400e+06 |
| 2096 | New Zealand | NZL | 2014 | 4.516500e+06 |
| 2097 | New Zealand | NZL | 2013 | 4.442100e+06 |
| 2098 | New Zealand | NZL | 2012 | 4.408100e+06 |
| 2099 | New Zealand | NZL | 2011 | 4.384000e+06 |
| 2100 | New Zealand | NZL | 2010 | 4.350700e+06 |
| 2101 | Nicaragua | NIC | 2020 | 6.755895e+06 |
| 2102 | Nicaragua | NIC | 2019 | 6.663924e+06 |
| 2103 | Nicaragua | NIC | 2018 | 6.572233e+06 |
| 2104 | Nicaragua | NIC | 2017 | 6.480532e+06 |
| 2105 | Nicaragua | NIC | 2016 | 6.389235e+06 |
| 2106 | Nicaragua | NIC | 2015 | 6.298598e+06 |
| 2107 | Nicaragua | NIC | 2014 | 6.208676e+06 |
| 2108 | Nicaragua | NIC | 2013 | 6.119379e+06 |
| 2109 | Nicaragua | NIC | 2012 | 6.030607e+06 |
| 2110 | Nicaragua | NIC | 2011 | 5.942553e+06 |
| 2111 | Nicaragua | NIC | 2010 | 5.855734e+06 |
| 2112 | Niger | NER | 2020 | 2.433364e+07 |
| 2113 | Niger | NER | 2019 | 2.344339e+07 |
| 2114 | Niger | NER | 2018 | 2.257706e+07 |
| 2115 | Niger | NER | 2017 | 2.173792e+07 |
| 2116 | Niger | NER | 2016 | 2.092174e+07 |
| 2117 | Niger | NER | 2015 | 2.012812e+07 |
| 2118 | Niger | NER | 2014 | 1.937201e+07 |
| 2119 | Niger | NER | 2013 | 1.865320e+07 |
| 2120 | Niger | NER | 2012 | 1.795441e+07 |
| 2121 | Niger | NER | 2011 | 1.728311e+07 |
| 2122 | Niger | NER | 2010 | 1.664754e+07 |
| 2123 | Nigeria | NGA | 2020 | 2.083274e+08 |
| 2124 | Nigeria | NGA | 2019 | 2.033045e+08 |
| 2125 | Nigeria | NGA | 2018 | 1.983876e+08 |
| 2126 | Nigeria | NGA | 2017 | 1.934959e+08 |
| 2127 | Nigeria | NGA | 2016 | 1.886669e+08 |
| 2128 | Nigeria | NGA | 2015 | 1.839958e+08 |
| 2129 | Nigeria | NGA | 2014 | 1.793790e+08 |
| 2130 | Nigeria | NGA | 2013 | 1.747261e+08 |
| 2131 | Nigeria | NGA | 2012 | 1.700759e+08 |
| 2132 | Nigeria | NGA | 2011 | 1.654637e+08 |
| 2133 | Nigeria | NGA | 2010 | 1.609529e+08 |
| 2134 | North Macedonia | MKD | 2020 | 2.072531e+06 |
| 2135 | North Macedonia | MKD | 2019 | 2.076694e+06 |
| 2136 | North Macedonia | MKD | 2018 | 2.076217e+06 |
| 2137 | North Macedonia | MKD | 2017 | 2.074502e+06 |
| 2138 | North Macedonia | MKD | 2016 | 2.072490e+06 |
| 2139 | North Macedonia | MKD | 2015 | 2.070226e+06 |
| 2140 | North Macedonia | MKD | 2014 | 2.067471e+06 |
| 2141 | North Macedonia | MKD | 2013 | 2.064032e+06 |
| 2142 | North Macedonia | MKD | 2012 | 2.061044e+06 |
| 2143 | North Macedonia | MKD | 2011 | 2.058539e+06 |
| 2144 | North Macedonia | MKD | 2010 | 2.055004e+06 |
| 2145 | Northern Mariana Islands | MNP | 2020 | 4.958700e+04 |
| 2146 | Northern Mariana Islands | MNP | 2019 | 4.985800e+04 |
| 2147 | Northern Mariana Islands | MNP | 2018 | 5.030400e+04 |
| 2148 | Northern Mariana Islands | MNP | 2017 | 5.072900e+04 |
| 2149 | Northern Mariana Islands | MNP | 2016 | 5.113300e+04 |
| 2150 | Northern Mariana Islands | MNP | 2015 | 5.151400e+04 |
| 2151 | Northern Mariana Islands | MNP | 2014 | 5.185600e+04 |
| 2152 | Northern Mariana Islands | MNP | 2013 | 5.214100e+04 |
| 2153 | Northern Mariana Islands | MNP | 2012 | 5.235900e+04 |
| 2154 | Northern Mariana Islands | MNP | 2011 | 5.252000e+04 |
| 2155 | Northern Mariana Islands | MNP | 2010 | 5.408700e+04 |
| 2156 | Norway | NOR | 2020 | 5.379475e+06 |
| 2157 | Norway | NOR | 2019 | 5.347896e+06 |
| 2158 | Norway | NOR | 2018 | 5.311916e+06 |
| 2159 | Norway | NOR | 2017 | 5.276968e+06 |
| 2160 | Norway | NOR | 2016 | 5.234519e+06 |
| 2161 | Norway | NOR | 2015 | 5.188607e+06 |
| 2162 | Norway | NOR | 2014 | 5.137232e+06 |
| 2163 | Norway | NOR | 2013 | 5.079623e+06 |
| 2164 | Norway | NOR | 2012 | 5.018573e+06 |
| 2165 | Norway | NOR | 2011 | 4.953088e+06 |
| 2166 | Norway | NOR | 2010 | 4.889252e+06 |
| 2167 | Oman | OMN | 2020 | 4.543399e+06 |
| 2168 | Oman | OMN | 2019 | 4.602768e+06 |
| 2169 | Oman | OMN | 2018 | 4.601157e+06 |
| 2170 | Oman | OMN | 2017 | 4.541854e+06 |
| 2171 | Oman | OMN | 2016 | 4.398070e+06 |
| 2172 | Oman | OMN | 2015 | 4.191776e+06 |
| 2173 | Oman | OMN | 2014 | 4.009267e+06 |
| 2174 | Oman | OMN | 2013 | 3.816680e+06 |
| 2175 | Oman | OMN | 2012 | 3.535579e+06 |
| 2176 | Oman | OMN | 2011 | 3.206870e+06 |
| 2177 | Oman | OMN | 2010 | 2.881914e+06 |
| 2178 | Pakistan | PAK | 2020 | 2.271967e+08 |
| 2179 | Pakistan | PAK | 2019 | 2.232933e+08 |
| 2180 | Pakistan | PAK | 2018 | 2.197315e+08 |
| 2181 | Pakistan | PAK | 2017 | 2.163797e+08 |
| 2182 | Pakistan | PAK | 2016 | 2.135248e+08 |
| 2183 | Pakistan | PAK | 2015 | 2.109693e+08 |
| 2184 | Pakistan | PAK | 2014 | 2.082516e+08 |
| 2185 | Pakistan | PAK | 2013 | 2.053376e+08 |
| 2186 | Pakistan | PAK | 2012 | 2.022059e+08 |
| 2187 | Pakistan | PAK | 2011 | 1.986027e+08 |
| 2188 | Pakistan | PAK | 2010 | 1.944545e+08 |
| 2189 | Palau | PLW | 2020 | 1.797200e+04 |
| 2190 | Palau | PLW | 2019 | 1.791600e+04 |
| 2191 | Palau | PLW | 2018 | 1.786400e+04 |
| 2192 | Palau | PLW | 2017 | 1.783700e+04 |
| 2193 | Palau | PLW | 2016 | 1.781600e+04 |
| 2194 | Palau | PLW | 2015 | 1.779400e+04 |
| 2195 | Palau | PLW | 2014 | 1.779600e+04 |
| 2196 | Palau | PLW | 2013 | 1.780500e+04 |
| 2197 | Palau | PLW | 2012 | 1.794600e+04 |
| 2198 | Palau | PLW | 2011 | 1.824000e+04 |
| 2199 | Palau | PLW | 2010 | 1.854000e+04 |
| 2200 | Panama | PAN | 2020 | 4.294396e+06 |
| 2201 | Panama | PAN | 2019 | 4.232532e+06 |
| 2202 | Panama | PAN | 2018 | 4.165255e+06 |
| 2203 | Panama | PAN | 2017 | 4.096063e+06 |
| 2204 | Panama | PAN | 2016 | 4.026336e+06 |
| 2205 | Panama | PAN | 2015 | 3.957099e+06 |
| 2206 | Panama | PAN | 2014 | 3.888793e+06 |
| 2207 | Panama | PAN | 2013 | 3.821556e+06 |
| 2208 | Panama | PAN | 2012 | 3.754862e+06 |
| 2209 | Panama | PAN | 2011 | 3.688674e+06 |
| 2210 | Panama | PAN | 2010 | 3.623617e+06 |
| 2211 | Papua New Guinea | PNG | 2020 | 9.749640e+06 |
| 2212 | Papua New Guinea | PNG | 2019 | 9.542486e+06 |
| 2213 | Papua New Guinea | PNG | 2018 | 9.329227e+06 |
| 2214 | Papua New Guinea | PNG | 2017 | 9.114796e+06 |
| 2215 | Papua New Guinea | PNG | 2016 | 8.899169e+06 |
| 2216 | Papua New Guinea | PNG | 2015 | 8.682174e+06 |
| 2217 | Papua New Guinea | PNG | 2014 | 8.464153e+06 |
| 2218 | Papua New Guinea | PNG | 2013 | 8.245627e+06 |
| 2219 | Papua New Guinea | PNG | 2012 | 8.026545e+06 |
| 2220 | Papua New Guinea | PNG | 2011 | 7.806637e+06 |
| 2221 | Papua New Guinea | PNG | 2010 | 7.583269e+06 |
| 2222 | Paraguay | PRY | 2020 | 6.618695e+06 |
| 2223 | Paraguay | PRY | 2019 | 6.530026e+06 |
| 2224 | Paraguay | PRY | 2018 | 6.443328e+06 |
| 2225 | Paraguay | PRY | 2017 | 6.355404e+06 |
| 2226 | Paraguay | PRY | 2016 | 6.266615e+06 |
| 2227 | Paraguay | PRY | 2015 | 6.177950e+06 |
| 2228 | Paraguay | PRY | 2014 | 6.090721e+06 |
| 2229 | Paraguay | PRY | 2013 | 6.005652e+06 |
| 2230 | Paraguay | PRY | 2012 | 5.923322e+06 |
| 2231 | Paraguay | PRY | 2011 | 5.843939e+06 |
| 2232 | Paraguay | PRY | 2010 | 5.768613e+06 |
| 2233 | Peru | PER | 2020 | 3.330476e+07 |
| 2234 | Peru | PER | 2019 | 3.282486e+07 |
| 2235 | Peru | PER | 2018 | 3.220394e+07 |
| 2236 | Peru | PER | 2017 | 3.160549e+07 |
| 2237 | Peru | PER | 2016 | 3.113278e+07 |
| 2238 | Peru | PER | 2015 | 3.071186e+07 |
| 2239 | Peru | PER | 2014 | 3.035395e+07 |
| 2240 | Peru | PER | 2013 | 3.003881e+07 |
| 2241 | Peru | PER | 2012 | 2.974959e+07 |
| 2242 | Peru | PER | 2011 | 2.947772e+07 |
| 2243 | Peru | PER | 2010 | 2.922957e+07 |
| 2244 | Philippines | PHL | 2020 | 1.121910e+08 |
| 2245 | Philippines | PHL | 2019 | 1.103808e+08 |
| 2246 | Philippines | PHL | 2018 | 1.085688e+08 |
| 2247 | Philippines | PHL | 2017 | 1.067385e+08 |
| 2248 | Philippines | PHL | 2016 | 1.048753e+08 |
| 2249 | Philippines | PHL | 2015 | 1.030314e+08 |
| 2250 | Philippines | PHL | 2014 | 1.013252e+08 |
| 2251 | Philippines | PHL | 2013 | 9.970011e+07 |
| 2252 | Philippines | PHL | 2012 | 9.803232e+07 |
| 2253 | Philippines | PHL | 2011 | 9.633791e+07 |
| 2254 | Philippines | PHL | 2010 | 9.463670e+07 |
| 2255 | Poland | POL | 2020 | 3.789907e+07 |
| 2256 | Poland | POL | 2019 | 3.796548e+07 |
| 2257 | Poland | POL | 2018 | 3.797475e+07 |
| 2258 | Poland | POL | 2017 | 3.797483e+07 |
| 2259 | Poland | POL | 2016 | 3.797009e+07 |
| 2260 | Poland | POL | 2015 | 3.798641e+07 |
| 2261 | Poland | POL | 2014 | 3.801174e+07 |
| 2262 | Poland | POL | 2013 | 3.804020e+07 |
| 2263 | Poland | POL | 2012 | 3.806316e+07 |
| 2264 | Poland | POL | 2011 | 3.806326e+07 |
| 2265 | Poland | POL | 2010 | 3.804279e+07 |
| 2266 | Portugal | PRT | 2020 | 1.029708e+07 |
| 2267 | Portugal | PRT | 2019 | 1.028626e+07 |
| 2268 | Portugal | PRT | 2018 | 1.028382e+07 |
| 2269 | Portugal | PRT | 2017 | 1.030030e+07 |
| 2270 | Portugal | PRT | 2016 | 1.032545e+07 |
| 2271 | Portugal | PRT | 2015 | 1.035808e+07 |
| 2272 | Portugal | PRT | 2014 | 1.040106e+07 |
| 2273 | Portugal | PRT | 2013 | 1.045730e+07 |
| 2274 | Portugal | PRT | 2012 | 1.051484e+07 |
| 2275 | Portugal | PRT | 2011 | 1.055756e+07 |
| 2276 | Portugal | PRT | 2010 | 1.057310e+07 |
| 2277 | Puerto Rico | PRI | 2020 | 3.281557e+06 |
| 2278 | Puerto Rico | PRI | 2019 | 3.193694e+06 |
| 2279 | Puerto Rico | PRI | 2018 | 3.193354e+06 |
| 2280 | Puerto Rico | PRI | 2017 | 3.325286e+06 |
| 2281 | Puerto Rico | PRI | 2016 | 3.406672e+06 |
| 2282 | Puerto Rico | PRI | 2015 | 3.473232e+06 |
| 2283 | Puerto Rico | PRI | 2014 | 3.534874e+06 |
| 2284 | Puerto Rico | PRI | 2013 | 3.593077e+06 |
| 2285 | Puerto Rico | PRI | 2012 | 3.634488e+06 |
| 2286 | Puerto Rico | PRI | 2011 | 3.678732e+06 |
| 2287 | Puerto Rico | PRI | 2010 | 3.721525e+06 |
| 2288 | Qatar | QAT | 2020 | 2.760385e+06 |
| 2289 | Qatar | QAT | 2019 | 2.807235e+06 |
| 2290 | Qatar | QAT | 2018 | 2.766732e+06 |
| 2291 | Qatar | QAT | 2017 | 2.711755e+06 |
| 2292 | Qatar | QAT | 2016 | 2.595166e+06 |
| 2293 | Qatar | QAT | 2015 | 2.414573e+06 |
| 2294 | Qatar | QAT | 2014 | 2.214465e+06 |
| 2295 | Qatar | QAT | 2013 | 2.035501e+06 |
| 2296 | Qatar | QAT | 2012 | 1.905660e+06 |
| 2297 | Qatar | QAT | 2011 | 1.804171e+06 |
| 2298 | Qatar | QAT | 2010 | 1.713504e+06 |
| 2299 | Romania | ROU | 2020 | 1.926525e+07 |
| 2300 | Romania | ROU | 2019 | 1.937165e+07 |
| 2301 | Romania | ROU | 2018 | 1.947397e+07 |
| 2302 | Romania | ROU | 2017 | 1.958872e+07 |
| 2303 | Romania | ROU | 2016 | 1.970227e+07 |
| 2304 | Romania | ROU | 2015 | 1.981562e+07 |
| 2305 | Romania | ROU | 2014 | 1.990898e+07 |
| 2306 | Romania | ROU | 2013 | 1.998369e+07 |
| 2307 | Romania | ROU | 2012 | 2.005804e+07 |
| 2308 | Romania | ROU | 2011 | 2.014753e+07 |
| 2309 | Romania | ROU | 2010 | 2.024687e+07 |
| 2310 | Russian Federation | RUS | 2020 | 1.440731e+08 |
| 2311 | Russian Federation | RUS | 2019 | 1.444063e+08 |
| 2312 | Russian Federation | RUS | 2018 | 1.444779e+08 |
| 2313 | Russian Federation | RUS | 2017 | 1.444967e+08 |
| 2314 | Russian Federation | RUS | 2016 | 1.443424e+08 |
| 2315 | Russian Federation | RUS | 2015 | 1.440969e+08 |
| 2316 | Russian Federation | RUS | 2014 | 1.438197e+08 |
| 2317 | Russian Federation | RUS | 2013 | 1.435070e+08 |
| 2318 | Russian Federation | RUS | 2012 | 1.432017e+08 |
| 2319 | Russian Federation | RUS | 2011 | 1.429609e+08 |
| 2320 | Russian Federation | RUS | 2010 | 1.428495e+08 |
| 2321 | Rwanda | RWA | 2020 | 1.314636e+07 |
| 2322 | Rwanda | RWA | 2019 | 1.283503e+07 |
| 2323 | Rwanda | RWA | 2018 | 1.253181e+07 |
| 2324 | Rwanda | RWA | 2017 | 1.223034e+07 |
| 2325 | Rwanda | RWA | 2016 | 1.193090e+07 |
| 2326 | Rwanda | RWA | 2015 | 1.164296e+07 |
| 2327 | Rwanda | RWA | 2014 | 1.136845e+07 |
| 2328 | Rwanda | RWA | 2013 | 1.110135e+07 |
| 2329 | Rwanda | RWA | 2012 | 1.084033e+07 |
| 2330 | Rwanda | RWA | 2011 | 1.057693e+07 |
| 2331 | Rwanda | RWA | 2010 | 1.030903e+07 |
| 2332 | Samoa | WSM | 2020 | 2.149290e+05 |
| 2333 | Samoa | WSM | 2019 | 2.119050e+05 |
| 2334 | Samoa | WSM | 2018 | 2.097010e+05 |
| 2335 | Samoa | WSM | 2017 | 2.076300e+05 |
| 2336 | Samoa | WSM | 2016 | 2.055440e+05 |
| 2337 | Samoa | WSM | 2015 | 2.035710e+05 |
| 2338 | Samoa | WSM | 2014 | 2.017570e+05 |
| 2339 | Samoa | WSM | 2013 | 1.999390e+05 |
| 2340 | Samoa | WSM | 2012 | 1.981240e+05 |
| 2341 | Samoa | WSM | 2011 | 1.963510e+05 |
| 2342 | Samoa | WSM | 2010 | 1.946720e+05 |
| 2343 | San Marino | SMR | 2020 | 3.400700e+04 |
| 2344 | San Marino | SMR | 2019 | 3.417800e+04 |
| 2345 | San Marino | SMR | 2018 | 3.415600e+04 |
| 2346 | San Marino | SMR | 2017 | 3.405600e+04 |
| 2347 | San Marino | SMR | 2016 | 3.383400e+04 |
| 2348 | San Marino | SMR | 2015 | 3.357000e+04 |
| 2349 | San Marino | SMR | 2014 | 3.338900e+04 |
| 2350 | San Marino | SMR | 2013 | 3.328500e+04 |
| 2351 | San Marino | SMR | 2012 | 3.313200e+04 |
| 2352 | San Marino | SMR | 2011 | 3.249500e+04 |
| 2353 | San Marino | SMR | 2010 | 3.160800e+04 |
| 2354 | Sao Tome and Principe | STP | 2020 | 2.186410e+05 |
| 2355 | Sao Tome and Principe | STP | 2019 | 2.145990e+05 |
| 2356 | Sao Tome and Principe | STP | 2018 | 2.113440e+05 |
| 2357 | Sao Tome and Principe | STP | 2017 | 2.080360e+05 |
| 2358 | Sao Tome and Principe | STP | 2016 | 2.046320e+05 |
| 2359 | Sao Tome and Principe | STP | 2015 | 2.011240e+05 |
| 2360 | Sao Tome and Principe | STP | 2014 | 1.974970e+05 |
| 2361 | Sao Tome and Principe | STP | 2013 | 1.937570e+05 |
| 2362 | Sao Tome and Principe | STP | 2012 | 1.899240e+05 |
| 2363 | Sao Tome and Principe | STP | 2011 | 1.860440e+05 |
| 2364 | Sao Tome and Principe | STP | 2010 | 1.821380e+05 |
| 2365 | Saudi Arabia | SAU | 2020 | 3.599711e+07 |
| 2366 | Saudi Arabia | SAU | 2019 | 3.582736e+07 |
| 2367 | Saudi Arabia | SAU | 2018 | 3.501813e+07 |
| 2368 | Saudi Arabia | SAU | 2017 | 3.419312e+07 |
| 2369 | Saudi Arabia | SAU | 2016 | 3.341627e+07 |
| 2370 | Saudi Arabia | SAU | 2015 | 3.274985e+07 |
| 2371 | Saudi Arabia | SAU | 2014 | 3.212556e+07 |
| 2372 | Saudi Arabia | SAU | 2013 | 3.148250e+07 |
| 2373 | Saudi Arabia | SAU | 2012 | 3.082154e+07 |
| 2374 | Saudi Arabia | SAU | 2011 | 3.015094e+07 |
| 2375 | Saudi Arabia | SAU | 2010 | 2.941193e+07 |
| 2376 | Senegal | SEN | 2020 | 1.643612e+07 |
| 2377 | Senegal | SEN | 2019 | 1.600078e+07 |
| 2378 | Senegal | SEN | 2018 | 1.557491e+07 |
| 2379 | Senegal | SEN | 2017 | 1.515779e+07 |
| 2380 | Senegal | SEN | 2016 | 1.475136e+07 |
| 2381 | Senegal | SEN | 2015 | 1.435618e+07 |
| 2382 | Senegal | SEN | 2014 | 1.397031e+07 |
| 2383 | Senegal | SEN | 2013 | 1.359557e+07 |
| 2384 | Senegal | SEN | 2012 | 1.323183e+07 |
| 2385 | Senegal | SEN | 2011 | 1.287588e+07 |
| 2386 | Senegal | SEN | 2010 | 1.253012e+07 |
| 2387 | Serbia | SRB | 2020 | 6.899126e+06 |
| 2388 | Serbia | SRB | 2019 | 6.945235e+06 |
| 2389 | Serbia | SRB | 2018 | 6.982604e+06 |
| 2390 | Serbia | SRB | 2017 | 7.020858e+06 |
| 2391 | Serbia | SRB | 2016 | 7.058322e+06 |
| 2392 | Serbia | SRB | 2015 | 7.095383e+06 |
| 2393 | Serbia | SRB | 2014 | 7.130576e+06 |
| 2394 | Serbia | SRB | 2013 | 7.164132e+06 |
| 2395 | Serbia | SRB | 2012 | 7.199077e+06 |
| 2396 | Serbia | SRB | 2011 | 7.234099e+06 |
| 2397 | Serbia | SRB | 2010 | 7.291436e+06 |
| 2398 | Seychelles | SYC | 2020 | 9.846200e+04 |
| 2399 | Seychelles | SYC | 2019 | 9.762500e+04 |
| 2400 | Seychelles | SYC | 2018 | 9.676200e+04 |
| 2401 | Seychelles | SYC | 2017 | 9.584300e+04 |
| 2402 | Seychelles | SYC | 2016 | 9.467700e+04 |
| 2403 | Seychelles | SYC | 2015 | 9.341900e+04 |
| 2404 | Seychelles | SYC | 2014 | 9.135900e+04 |
| 2405 | Seychelles | SYC | 2013 | 8.994900e+04 |
| 2406 | Seychelles | SYC | 2012 | 8.830300e+04 |
| 2407 | Seychelles | SYC | 2011 | 8.744100e+04 |
| 2408 | Seychelles | SYC | 2010 | 8.977000e+04 |
| 2409 | Sierra Leone | SLE | 2020 | 8.233970e+06 |
| 2410 | Sierra Leone | SLE | 2019 | 8.046828e+06 |
| 2411 | Sierra Leone | SLE | 2018 | 7.861281e+06 |
| 2412 | Sierra Leone | SLE | 2017 | 7.677565e+06 |
| 2413 | Sierra Leone | SLE | 2016 | 7.493913e+06 |
| 2414 | Sierra Leone | SLE | 2015 | 7.314773e+06 |
| 2415 | Sierra Leone | SLE | 2014 | 7.140688e+06 |
| 2416 | Sierra Leone | SLE | 2013 | 6.964859e+06 |
| 2417 | Sierra Leone | SLE | 2012 | 6.788587e+06 |
| 2418 | Sierra Leone | SLE | 2011 | 6.612385e+06 |
| 2419 | Sierra Leone | SLE | 2010 | 6.436698e+06 |
| 2420 | Singapore | SGP | 2020 | 5.685807e+06 |
| 2421 | Singapore | SGP | 2019 | 5.703569e+06 |
| 2422 | Singapore | SGP | 2018 | 5.638676e+06 |
| 2423 | Singapore | SGP | 2017 | 5.612253e+06 |
| 2424 | Singapore | SGP | 2016 | 5.607283e+06 |
| 2425 | Singapore | SGP | 2015 | 5.535002e+06 |
| 2426 | Singapore | SGP | 2014 | 5.469724e+06 |
| 2427 | Singapore | SGP | 2013 | 5.399162e+06 |
| 2428 | Singapore | SGP | 2012 | 5.312437e+06 |
| 2429 | Singapore | SGP | 2011 | 5.183688e+06 |
| 2430 | Singapore | SGP | 2010 | 5.076732e+06 |
| 2431 | Sint Maarten (Dutch part) | SXM | 2020 | 4.231000e+04 |
| 2432 | Sint Maarten (Dutch part) | SXM | 2019 | 4.160800e+04 |
| 2433 | Sint Maarten (Dutch part) | SXM | 2018 | 4.089500e+04 |
| 2434 | Sint Maarten (Dutch part) | SXM | 2017 | 4.057400e+04 |
| 2435 | Sint Maarten (Dutch part) | SXM | 2016 | 3.996900e+04 |
| 2436 | Sint Maarten (Dutch part) | SXM | 2015 | 3.882500e+04 |
| 2437 | Sint Maarten (Dutch part) | SXM | 2014 | 3.768500e+04 |
| 2438 | Sint Maarten (Dutch part) | SXM | 2013 | 3.660700e+04 |
| 2439 | Sint Maarten (Dutch part) | SXM | 2012 | 3.464000e+04 |
| 2440 | Sint Maarten (Dutch part) | SXM | 2011 | 3.343500e+04 |
| 2441 | Sint Maarten (Dutch part) | SXM | 2010 | 3.405600e+04 |
| 2442 | Slovak Republic | SVK | 2020 | 5.458827e+06 |
| 2443 | Slovak Republic | SVK | 2019 | 5.454147e+06 |
| 2444 | Slovak Republic | SVK | 2018 | 5.446771e+06 |
| 2445 | Slovak Republic | SVK | 2017 | 5.439232e+06 |
| 2446 | Slovak Republic | SVK | 2016 | 5.430798e+06 |
| 2447 | Slovak Republic | SVK | 2015 | 5.423801e+06 |
| 2448 | Slovak Republic | SVK | 2014 | 5.418649e+06 |
| 2449 | Slovak Republic | SVK | 2013 | 5.413393e+06 |
| 2450 | Slovak Republic | SVK | 2012 | 5.407579e+06 |
| 2451 | Slovak Republic | SVK | 2011 | 5.398384e+06 |
| 2452 | Slovak Republic | SVK | 2010 | 5.391428e+06 |
| 2453 | Slovenia | SVN | 2020 | 2.102419e+06 |
| 2454 | Slovenia | SVN | 2019 | 2.088385e+06 |
| 2455 | Slovenia | SVN | 2018 | 2.073894e+06 |
| 2456 | Slovenia | SVN | 2017 | 2.066388e+06 |
| 2457 | Slovenia | SVN | 2016 | 2.065042e+06 |
| 2458 | Slovenia | SVN | 2015 | 2.063531e+06 |
| 2459 | Slovenia | SVN | 2014 | 2.061980e+06 |
| 2460 | Slovenia | SVN | 2013 | 2.059953e+06 |
| 2461 | Slovenia | SVN | 2012 | 2.057159e+06 |
| 2462 | Slovenia | SVN | 2011 | 2.052843e+06 |
| 2463 | Slovenia | SVN | 2010 | 2.048583e+06 |
| 2464 | Solomon Islands | SLB | 2020 | 6.911910e+05 |
| 2465 | Solomon Islands | SLB | 2019 | 6.749930e+05 |
| 2466 | Solomon Islands | SLB | 2018 | 6.592490e+05 |
| 2467 | Solomon Islands | SLB | 2017 | 6.436340e+05 |
| 2468 | Solomon Islands | SLB | 2016 | 6.281020e+05 |
| 2469 | Solomon Islands | SLB | 2015 | 6.126600e+05 |
| 2470 | Solomon Islands | SLB | 2014 | 5.973750e+05 |
| 2471 | Solomon Islands | SLB | 2013 | 5.823650e+05 |
| 2472 | Solomon Islands | SLB | 2012 | 5.677630e+05 |
| 2473 | Solomon Islands | SLB | 2011 | 5.537210e+05 |
| 2474 | Solomon Islands | SLB | 2010 | 5.403940e+05 |
| 2475 | Somalia | SOM | 2020 | 1.653702e+07 |
| 2476 | Somalia | SOM | 2019 | 1.598130e+07 |
| 2477 | Somalia | SOM | 2018 | 1.541109e+07 |
| 2478 | Somalia | SOM | 2017 | 1.486422e+07 |
| 2479 | Somalia | SOM | 2016 | 1.429285e+07 |
| 2480 | Somalia | SOM | 2015 | 1.376391e+07 |
| 2481 | Somalia | SOM | 2014 | 1.330924e+07 |
| 2482 | Somalia | SOM | 2013 | 1.285248e+07 |
| 2483 | Somalia | SOM | 2012 | 1.244033e+07 |
| 2484 | Somalia | SOM | 2011 | 1.221684e+07 |
| 2485 | Somalia | SOM | 2010 | 1.202665e+07 |
| 2486 | South Africa | ZAF | 2020 | 5.880193e+07 |
| 2487 | South Africa | ZAF | 2019 | 5.808706e+07 |
| 2488 | South Africa | ZAF | 2018 | 5.733964e+07 |
| 2489 | South Africa | ZAF | 2017 | 5.664121e+07 |
| 2490 | South Africa | ZAF | 2016 | 5.642227e+07 |
| 2491 | South Africa | ZAF | 2015 | 5.587650e+07 |
| 2492 | South Africa | ZAF | 2014 | 5.472955e+07 |
| 2493 | South Africa | ZAF | 2013 | 5.387362e+07 |
| 2494 | South Africa | ZAF | 2012 | 5.314503e+07 |
| 2495 | South Africa | ZAF | 2011 | 5.244332e+07 |
| 2496 | South Africa | ZAF | 2010 | 5.178492e+07 |
| 2497 | South Sudan | SSD | 2020 | 1.060623e+07 |
| 2498 | South Sudan | SSD | 2019 | 1.044767e+07 |
| 2499 | South Sudan | SSD | 2018 | 1.039533e+07 |
| 2500 | South Sudan | SSD | 2017 | 1.065823e+07 |
| 2501 | South Sudan | SSD | 2016 | 1.106610e+07 |
| 2502 | South Sudan | SSD | 2015 | 1.119430e+07 |
| 2503 | South Sudan | SSD | 2014 | 1.121328e+07 |
| 2504 | South Sudan | SSD | 2013 | 1.110603e+07 |
| 2505 | South Sudan | SSD | 2012 | 1.070160e+07 |
| 2506 | South Sudan | SSD | 2011 | 1.024305e+07 |
| 2507 | South Sudan | SSD | 2010 | 9.714419e+06 |
| 2508 | Spain | ESP | 2020 | 4.736566e+07 |
| 2509 | Spain | ESP | 2019 | 4.713484e+07 |
| 2510 | Spain | ESP | 2018 | 4.679775e+07 |
| 2511 | Spain | ESP | 2017 | 4.659324e+07 |
| 2512 | Spain | ESP | 2016 | 4.648406e+07 |
| 2513 | Spain | ESP | 2015 | 4.644483e+07 |
| 2514 | Spain | ESP | 2014 | 4.648088e+07 |
| 2515 | Spain | ESP | 2013 | 4.662004e+07 |
| 2516 | Spain | ESP | 2012 | 4.677306e+07 |
| 2517 | Spain | ESP | 2011 | 4.674270e+07 |
| 2518 | Spain | ESP | 2010 | 4.657690e+07 |
| 2519 | Sri Lanka | LKA | 2020 | 2.191900e+07 |
| 2520 | Sri Lanka | LKA | 2019 | 2.180300e+07 |
| 2521 | Sri Lanka | LKA | 2018 | 2.167000e+07 |
| 2522 | Sri Lanka | LKA | 2017 | 2.150681e+07 |
| 2523 | Sri Lanka | LKA | 2016 | 2.142549e+07 |
| 2524 | Sri Lanka | LKA | 2015 | 2.133670e+07 |
| 2525 | Sri Lanka | LKA | 2014 | 2.123946e+07 |
| 2526 | Sri Lanka | LKA | 2013 | 2.113176e+07 |
| 2527 | Sri Lanka | LKA | 2012 | 2.101715e+07 |
| 2528 | Sri Lanka | LKA | 2011 | 2.085974e+07 |
| 2529 | Sri Lanka | LKA | 2010 | 2.066856e+07 |
| 2530 | St. Kitts and Nevis | KNA | 2020 | 4.764200e+04 |
| 2531 | St. Kitts and Nevis | KNA | 2019 | 4.771200e+04 |
| 2532 | St. Kitts and Nevis | KNA | 2018 | 4.776100e+04 |
| 2533 | St. Kitts and Nevis | KNA | 2017 | 4.778500e+04 |
| 2534 | St. Kitts and Nevis | KNA | 2016 | 4.778800e+04 |
| 2535 | St. Kitts and Nevis | KNA | 2015 | 4.779000e+04 |
| 2536 | St. Kitts and Nevis | KNA | 2014 | 4.778900e+04 |
| 2537 | St. Kitts and Nevis | KNA | 2013 | 4.776700e+04 |
| 2538 | St. Kitts and Nevis | KNA | 2012 | 4.772700e+04 |
| 2539 | St. Kitts and Nevis | KNA | 2011 | 4.758100e+04 |
| 2540 | St. Kitts and Nevis | KNA | 2010 | 4.740300e+04 |
| 2541 | St. Lucia | LCA | 2020 | 1.792370e+05 |
| 2542 | St. Lucia | LCA | 2019 | 1.785830e+05 |
| 2543 | St. Lucia | LCA | 2018 | 1.778880e+05 |
| 2544 | St. Lucia | LCA | 2017 | 1.771630e+05 |
| 2545 | St. Lucia | LCA | 2016 | 1.764130e+05 |
| 2546 | St. Lucia | LCA | 2015 | 1.756230e+05 |
| 2547 | St. Lucia | LCA | 2014 | 1.748040e+05 |
| 2548 | St. Lucia | LCA | 2013 | 1.739780e+05 |
| 2549 | St. Lucia | LCA | 2012 | 1.731240e+05 |
| 2550 | St. Lucia | LCA | 2011 | 1.721450e+05 |
| 2551 | St. Lucia | LCA | 2010 | 1.709350e+05 |
| 2552 | St. Martin (French part) | MAF | 2020 | 3.255300e+04 |
| 2553 | St. Martin (French part) | MAF | 2019 | 3.312100e+04 |
| 2554 | St. Martin (French part) | MAF | 2018 | 3.385200e+04 |
| 2555 | St. Martin (French part) | MAF | 2017 | 3.449600e+04 |
| 2556 | St. Martin (French part) | MAF | 2016 | 3.481100e+04 |
| 2557 | St. Martin (French part) | MAF | 2015 | 3.502000e+04 |
| 2558 | St. Martin (French part) | MAF | 2014 | 3.526100e+04 |
| 2559 | St. Martin (French part) | MAF | 2013 | 3.563900e+04 |
| 2560 | St. Martin (French part) | MAF | 2012 | 3.602600e+04 |
| 2561 | St. Martin (French part) | MAF | 2011 | 3.635000e+04 |
| 2562 | St. Martin (French part) | MAF | 2010 | 3.645800e+04 |
| 2563 | St. Vincent and the Grenadines | VCT | 2020 | 1.046320e+05 |
| 2564 | St. Vincent and the Grenadines | VCT | 2019 | 1.049240e+05 |
| 2565 | St. Vincent and the Grenadines | VCT | 2018 | 1.052810e+05 |
| 2566 | St. Vincent and the Grenadines | VCT | 2017 | 1.055490e+05 |
| 2567 | St. Vincent and the Grenadines | VCT | 2016 | 1.059630e+05 |
| 2568 | St. Vincent and the Grenadines | VCT | 2015 | 1.064820e+05 |
| 2569 | St. Vincent and the Grenadines | VCT | 2014 | 1.069120e+05 |
| 2570 | St. Vincent and the Grenadines | VCT | 2013 | 1.074500e+05 |
| 2571 | St. Vincent and the Grenadines | VCT | 2012 | 1.080830e+05 |
| 2572 | St. Vincent and the Grenadines | VCT | 2011 | 1.087030e+05 |
| 2573 | St. Vincent and the Grenadines | VCT | 2010 | 1.093080e+05 |
| 2574 | Sudan | SDN | 2020 | 4.444049e+07 |
| 2575 | Sudan | SDN | 2019 | 4.323209e+07 |
| 2576 | Sudan | SDN | 2018 | 4.199906e+07 |
| 2577 | Sudan | SDN | 2017 | 4.067983e+07 |
| 2578 | Sudan | SDN | 2016 | 3.937717e+07 |
| 2579 | Sudan | SDN | 2015 | 3.817118e+07 |
| 2580 | Sudan | SDN | 2014 | 3.700324e+07 |
| 2581 | Sudan | SDN | 2013 | 3.599070e+07 |
| 2582 | Sudan | SDN | 2012 | 3.515979e+07 |
| 2583 | Sudan | SDN | 2011 | 3.441962e+07 |
| 2584 | Sudan | SDN | 2010 | 3.373993e+07 |
| 2585 | Suriname | SUR | 2020 | 6.070650e+05 |
| 2586 | Suriname | SUR | 2019 | 6.003010e+05 |
| 2587 | Suriname | SUR | 2018 | 5.937150e+05 |
| 2588 | Suriname | SUR | 2017 | 5.875590e+05 |
| 2589 | Suriname | SUR | 2016 | 5.814530e+05 |
| 2590 | Suriname | SUR | 2015 | 5.754750e+05 |
| 2591 | Suriname | SUR | 2014 | 5.696820e+05 |
| 2592 | Suriname | SUR | 2013 | 5.639470e+05 |
| 2593 | Suriname | SUR | 2012 | 5.581110e+05 |
| 2594 | Suriname | SUR | 2011 | 5.521460e+05 |
| 2595 | Suriname | SUR | 2010 | 5.460800e+05 |
| 2596 | Sweden | SWE | 2020 | 1.035344e+07 |
| 2597 | Sweden | SWE | 2019 | 1.027889e+07 |
| 2598 | Sweden | SWE | 2018 | 1.017521e+07 |
| 2599 | Sweden | SWE | 2017 | 1.005770e+07 |
| 2600 | Sweden | SWE | 2016 | 9.923085e+06 |
| 2601 | Sweden | SWE | 2015 | 9.799186e+06 |
| 2602 | Sweden | SWE | 2014 | 9.696110e+06 |
| 2603 | Sweden | SWE | 2013 | 9.600379e+06 |
| 2604 | Sweden | SWE | 2012 | 9.519374e+06 |
| 2605 | Sweden | SWE | 2011 | 9.449213e+06 |
| 2606 | Sweden | SWE | 2010 | 9.378126e+06 |
| 2607 | Switzerland | CHE | 2020 | 8.638167e+06 |
| 2608 | Switzerland | CHE | 2019 | 8.575280e+06 |
| 2609 | Switzerland | CHE | 2018 | 8.514329e+06 |
| 2610 | Switzerland | CHE | 2017 | 8.451840e+06 |
| 2611 | Switzerland | CHE | 2016 | 8.373338e+06 |
| 2612 | Switzerland | CHE | 2015 | 8.282396e+06 |
| 2613 | Switzerland | CHE | 2014 | 8.188649e+06 |
| 2614 | Switzerland | CHE | 2013 | 8.089346e+06 |
| 2615 | Switzerland | CHE | 2012 | 7.996861e+06 |
| 2616 | Switzerland | CHE | 2011 | 7.912398e+06 |
| 2617 | Switzerland | CHE | 2010 | 7.824909e+06 |
| 2618 | Syrian Arab Republic | SYR | 2020 | 2.077260e+07 |
| 2619 | Syrian Arab Republic | SYR | 2019 | 2.009825e+07 |
| 2620 | Syrian Arab Republic | SYR | 2018 | 1.933346e+07 |
| 2621 | Syrian Arab Republic | SYR | 2017 | 1.898337e+07 |
| 2622 | Syrian Arab Republic | SYR | 2016 | 1.896425e+07 |
| 2623 | Syrian Arab Republic | SYR | 2015 | 1.920518e+07 |
| 2624 | Syrian Arab Republic | SYR | 2014 | 2.007223e+07 |
| 2625 | Syrian Arab Republic | SYR | 2013 | 2.149582e+07 |
| 2626 | Syrian Arab Republic | SYR | 2012 | 2.260558e+07 |
| 2627 | Syrian Arab Republic | SYR | 2011 | 2.273073e+07 |
| 2628 | Syrian Arab Republic | SYR | 2010 | 2.233756e+07 |
| 2629 | Tajikistan | TJK | 2020 | 9.543207e+06 |
| 2630 | Tajikistan | TJK | 2019 | 9.337003e+06 |
| 2631 | Tajikistan | TJK | 2018 | 9.128132e+06 |
| 2632 | Tajikistan | TJK | 2017 | 8.925525e+06 |
| 2633 | Tajikistan | TJK | 2016 | 8.725318e+06 |
| 2634 | Tajikistan | TJK | 2015 | 8.524063e+06 |
| 2635 | Tajikistan | TJK | 2014 | 8.326348e+06 |
| 2636 | Tajikistan | TJK | 2013 | 8.136610e+06 |
| 2637 | Tajikistan | TJK | 2012 | 7.956382e+06 |
| 2638 | Tajikistan | TJK | 2011 | 7.784819e+06 |
| 2639 | Tajikistan | TJK | 2010 | 7.621779e+06 |
| 2640 | Tanzania | TZA | 2020 | 6.170452e+07 |
| 2641 | Tanzania | TZA | 2019 | 5.987258e+07 |
| 2642 | Tanzania | TZA | 2018 | 5.809044e+07 |
| 2643 | Tanzania | TZA | 2017 | 5.626703e+07 |
| 2644 | Tanzania | TZA | 2016 | 5.440180e+07 |
| 2645 | Tanzania | TZA | 2015 | 5.254282e+07 |
| 2646 | Tanzania | TZA | 2014 | 5.081455e+07 |
| 2647 | Tanzania | TZA | 2013 | 4.925364e+07 |
| 2648 | Tanzania | TZA | 2012 | 4.778614e+07 |
| 2649 | Tanzania | TZA | 2011 | 4.641603e+07 |
| 2650 | Tanzania | TZA | 2010 | 4.511053e+07 |
| 2651 | Thailand | THA | 2020 | 7.147566e+07 |
| 2652 | Thailand | THA | 2019 | 7.130776e+07 |
| 2653 | Thailand | THA | 2018 | 7.112780e+07 |
| 2654 | Thailand | THA | 2017 | 7.089820e+07 |
| 2655 | Thailand | THA | 2016 | 7.060704e+07 |
| 2656 | Thailand | THA | 2015 | 7.029440e+07 |
| 2657 | Thailand | THA | 2014 | 6.996094e+07 |
| 2658 | Thailand | THA | 2013 | 6.957860e+07 |
| 2659 | Thailand | THA | 2012 | 6.915702e+07 |
| 2660 | Thailand | THA | 2011 | 6.871285e+07 |
| 2661 | Thailand | THA | 2010 | 6.827049e+07 |
| 2662 | Timor-Leste | TLS | 2020 | 1.299995e+06 |
| 2663 | Timor-Leste | TLS | 2019 | 1.280438e+06 |
| 2664 | Timor-Leste | TLS | 2018 | 1.261845e+06 |
| 2665 | Timor-Leste | TLS | 2017 | 1.243235e+06 |
| 2666 | Timor-Leste | TLS | 2016 | 1.224562e+06 |
| 2667 | Timor-Leste | TLS | 2015 | 1.205813e+06 |
| 2668 | Timor-Leste | TLS | 2014 | 1.184830e+06 |
| 2669 | Timor-Leste | TLS | 2013 | 1.161555e+06 |
| 2670 | Timor-Leste | TLS | 2012 | 1.137676e+06 |
| 2671 | Timor-Leste | TLS | 2011 | 1.112976e+06 |
| 2672 | Timor-Leste | TLS | 2010 | 1.088486e+06 |
| 2673 | Togo | TGO | 2020 | 8.442580e+06 |
| 2674 | Togo | TGO | 2019 | 8.243094e+06 |
| 2675 | Togo | TGO | 2018 | 8.046679e+06 |
| 2676 | Togo | TGO | 2017 | 7.852795e+06 |
| 2677 | Togo | TGO | 2016 | 7.661354e+06 |
| 2678 | Togo | TGO | 2015 | 7.473229e+06 |
| 2679 | Togo | TGO | 2014 | 7.288383e+06 |
| 2680 | Togo | TGO | 2013 | 7.106229e+06 |
| 2681 | Togo | TGO | 2012 | 6.926635e+06 |
| 2682 | Togo | TGO | 2011 | 6.748672e+06 |
| 2683 | Togo | TGO | 2010 | 6.571855e+06 |
| 2684 | Tonga | TON | 2020 | 1.052540e+05 |
| 2685 | Tonga | TON | 2019 | 1.049510e+05 |
| 2686 | Tonga | TON | 2018 | 1.051500e+05 |
| 2687 | Tonga | TON | 2017 | 1.054150e+05 |
| 2688 | Tonga | TON | 2016 | 1.057070e+05 |
| 2689 | Tonga | TON | 2015 | 1.061220e+05 |
| 2690 | Tonga | TON | 2014 | 1.066260e+05 |
| 2691 | Tonga | TON | 2013 | 1.070890e+05 |
| 2692 | Tonga | TON | 2012 | 1.075020e+05 |
| 2693 | Tonga | TON | 2011 | 1.076110e+05 |
| 2694 | Tonga | TON | 2010 | 1.073830e+05 |
| 2695 | Trinidad and Tobago | TTO | 2020 | 1.518147e+06 |
| 2696 | Trinidad and Tobago | TTO | 2019 | 1.519955e+06 |
| 2697 | Trinidad and Tobago | TTO | 2018 | 1.504709e+06 |
| 2698 | Trinidad and Tobago | TTO | 2017 | 1.478607e+06 |
| 2699 | Trinidad and Tobago | TTO | 2016 | 1.469330e+06 |
| 2700 | Trinidad and Tobago | TTO | 2015 | 1.460177e+06 |
| 2701 | Trinidad and Tobago | TTO | 2014 | 1.450661e+06 |
| 2702 | Trinidad and Tobago | TTO | 2013 | 1.440729e+06 |
| 2703 | Trinidad and Tobago | TTO | 2012 | 1.430377e+06 |
| 2704 | Trinidad and Tobago | TTO | 2011 | 1.420020e+06 |
| 2705 | Trinidad and Tobago | TTO | 2010 | 1.410296e+06 |
| 2706 | Tunisia | TUN | 2020 | 1.216172e+07 |
| 2707 | Tunisia | TUN | 2019 | 1.204931e+07 |
| 2708 | Tunisia | TUN | 2018 | 1.193304e+07 |
| 2709 | Tunisia | TUN | 2017 | 1.181144e+07 |
| 2710 | Tunisia | TUN | 2016 | 1.168567e+07 |
| 2711 | Tunisia | TUN | 2015 | 1.155778e+07 |
| 2712 | Tunisia | TUN | 2014 | 1.142895e+07 |
| 2713 | Tunisia | TUN | 2013 | 1.130028e+07 |
| 2714 | Tunisia | TUN | 2012 | 1.117438e+07 |
| 2715 | Tunisia | TUN | 2011 | 1.103253e+07 |
| 2716 | Tunisia | TUN | 2010 | 1.089506e+07 |
| 2717 | Turkiye | TUR | 2020 | 8.338468e+07 |
| 2718 | Turkiye | TUR | 2019 | 8.257944e+07 |
| 2719 | Turkiye | TUR | 2018 | 8.140720e+07 |
| 2720 | Turkiye | TUR | 2017 | 8.031270e+07 |
| 2721 | Turkiye | TUR | 2016 | 7.927796e+07 |
| 2722 | Turkiye | TUR | 2015 | 7.821848e+07 |
| 2723 | Turkiye | TUR | 2014 | 7.718188e+07 |
| 2724 | Turkiye | TUR | 2013 | 7.614762e+07 |
| 2725 | Turkiye | TUR | 2012 | 7.517583e+07 |
| 2726 | Turkiye | TUR | 2011 | 7.422363e+07 |
| 2727 | Turkiye | TUR | 2010 | 7.314215e+07 |
| 2728 | Turkmenistan | TKM | 2020 | 6.250438e+06 |
| 2729 | Turkmenistan | TKM | 2019 | 6.158420e+06 |
| 2730 | Turkmenistan | TKM | 2018 | 6.065066e+06 |
| 2731 | Turkmenistan | TKM | 2017 | 5.968383e+06 |
| 2732 | Turkmenistan | TKM | 2016 | 5.868561e+06 |
| 2733 | Turkmenistan | TKM | 2015 | 5.766431e+06 |
| 2734 | Turkmenistan | TKM | 2014 | 5.663152e+06 |
| 2735 | Turkmenistan | TKM | 2013 | 5.560095e+06 |
| 2736 | Turkmenistan | TKM | 2012 | 5.458682e+06 |
| 2737 | Turkmenistan | TKM | 2011 | 5.360811e+06 |
| 2738 | Turkmenistan | TKM | 2010 | 5.267970e+06 |
| 2739 | Turks and Caicos Islands | TCA | 2020 | 4.427600e+04 |
| 2740 | Turks and Caicos Islands | TCA | 2019 | 4.308000e+04 |
| 2741 | Turks and Caicos Islands | TCA | 2018 | 4.148700e+04 |
| 2742 | Turks and Caicos Islands | TCA | 2017 | 3.984400e+04 |
| 2743 | Turks and Caicos Islands | TCA | 2016 | 3.824600e+04 |
| 2744 | Turks and Caicos Islands | TCA | 2015 | 3.653800e+04 |
| 2745 | Turks and Caicos Islands | TCA | 2014 | 3.498500e+04 |
| 2746 | Turks and Caicos Islands | TCA | 2013 | 3.359400e+04 |
| 2747 | Turks and Caicos Islands | TCA | 2012 | 3.208100e+04 |
| 2748 | Turks and Caicos Islands | TCA | 2011 | 3.081600e+04 |
| 2749 | Turks and Caicos Islands | TCA | 2010 | 2.972600e+04 |
| 2750 | Tuvalu | TUV | 2020 | 1.106900e+04 |
| 2751 | Tuvalu | TUV | 2019 | 1.095600e+04 |
| 2752 | Tuvalu | TUV | 2018 | 1.086500e+04 |
| 2753 | Tuvalu | TUV | 2017 | 1.082800e+04 |
| 2754 | Tuvalu | TUV | 2016 | 1.085200e+04 |
| 2755 | Tuvalu | TUV | 2015 | 1.087700e+04 |
| 2756 | Tuvalu | TUV | 2014 | 1.089900e+04 |
| 2757 | Tuvalu | TUV | 2013 | 1.091800e+04 |
| 2758 | Tuvalu | TUV | 2012 | 1.085400e+04 |
| 2759 | Tuvalu | TUV | 2011 | 1.070000e+04 |
| 2760 | Tuvalu | TUV | 2010 | 1.055000e+04 |
| 2761 | Uganda | UGA | 2020 | 4.440461e+07 |
| 2762 | Uganda | UGA | 2019 | 4.294908e+07 |
| 2763 | Uganda | UGA | 2018 | 4.151540e+07 |
| 2764 | Uganda | UGA | 2017 | 4.012708e+07 |
| 2765 | Uganda | UGA | 2016 | 3.874830e+07 |
| 2766 | Uganda | UGA | 2015 | 3.747736e+07 |
| 2767 | Uganda | UGA | 2014 | 3.633654e+07 |
| 2768 | Uganda | UGA | 2013 | 3.527357e+07 |
| 2769 | Uganda | UGA | 2012 | 3.427330e+07 |
| 2770 | Uganda | UGA | 2011 | 3.329574e+07 |
| 2771 | Uganda | UGA | 2010 | 3.234173e+07 |
| 2772 | Ukraine | UKR | 2020 | 4.413205e+07 |
| 2773 | Ukraine | UKR | 2019 | 4.438620e+07 |
| 2774 | Ukraine | UKR | 2018 | 4.462252e+07 |
| 2775 | Ukraine | UKR | 2017 | 4.483114e+07 |
| 2776 | Ukraine | UKR | 2016 | 4.500467e+07 |
| 2777 | Ukraine | UKR | 2015 | 4.515404e+07 |
| 2778 | Ukraine | UKR | 2014 | 4.527216e+07 |
| 2779 | Ukraine | UKR | 2013 | 4.548965e+07 |
| 2780 | Ukraine | UKR | 2012 | 4.559334e+07 |
| 2781 | Ukraine | UKR | 2011 | 4.570609e+07 |
| 2782 | Ukraine | UKR | 2010 | 4.587074e+07 |
| 2783 | United Arab Emirates | ARE | 2020 | 9.287289e+06 |
| 2784 | United Arab Emirates | ARE | 2019 | 9.211657e+06 |
| 2785 | United Arab Emirates | ARE | 2018 | 9.140169e+06 |
| 2786 | United Arab Emirates | ARE | 2017 | 9.068296e+06 |
| 2787 | United Arab Emirates | ARE | 2016 | 8.994263e+06 |
| 2788 | United Arab Emirates | ARE | 2015 | 8.916899e+06 |
| 2789 | United Arab Emirates | ARE | 2014 | 8.835951e+06 |
| 2790 | United Arab Emirates | ARE | 2013 | 8.751847e+06 |
| 2791 | United Arab Emirates | ARE | 2012 | 8.664969e+06 |
| 2792 | United Arab Emirates | ARE | 2011 | 8.575205e+06 |
| 2793 | United Arab Emirates | ARE | 2010 | 8.481771e+06 |
| 2794 | United Kingdom | GBR | 2020 | 6.708123e+07 |
| 2795 | United Kingdom | GBR | 2019 | 6.683633e+07 |
| 2796 | United Kingdom | GBR | 2018 | 6.646034e+07 |
| 2797 | United Kingdom | GBR | 2017 | 6.605886e+07 |
| 2798 | United Kingdom | GBR | 2016 | 6.561159e+07 |
| 2799 | United Kingdom | GBR | 2015 | 6.511622e+07 |
| 2800 | United Kingdom | GBR | 2014 | 6.460230e+07 |
| 2801 | United Kingdom | GBR | 2013 | 6.412827e+07 |
| 2802 | United Kingdom | GBR | 2012 | 6.370022e+07 |
| 2803 | United Kingdom | GBR | 2011 | 6.325881e+07 |
| 2804 | United Kingdom | GBR | 2010 | 6.276636e+07 |
| 2805 | United States | USA | 2020 | 3.315115e+08 |
| 2806 | United States | USA | 2019 | 3.283300e+08 |
| 2807 | United States | USA | 2018 | 3.268382e+08 |
| 2808 | United States | USA | 2017 | 3.251221e+08 |
| 2809 | United States | USA | 2016 | 3.230718e+08 |
| 2810 | United States | USA | 2015 | 3.207390e+08 |
| 2811 | United States | USA | 2014 | 3.183863e+08 |
| 2812 | United States | USA | 2013 | 3.160599e+08 |
| 2813 | United States | USA | 2012 | 3.138777e+08 |
| 2814 | United States | USA | 2011 | 3.115835e+08 |
| 2815 | United States | USA | 2010 | 3.093271e+08 |
| 2816 | Uruguay | URY | 2020 | 3.429086e+06 |
| 2817 | Uruguay | URY | 2019 | 3.428409e+06 |
| 2818 | Uruguay | URY | 2018 | 3.427042e+06 |
| 2819 | Uruguay | URY | 2017 | 3.422200e+06 |
| 2820 | Uruguay | URY | 2016 | 3.413766e+06 |
| 2821 | Uruguay | URY | 2015 | 3.402818e+06 |
| 2822 | Uruguay | URY | 2014 | 3.391662e+06 |
| 2823 | Uruguay | URY | 2013 | 3.381180e+06 |
| 2824 | Uruguay | URY | 2012 | 3.371133e+06 |
| 2825 | Uruguay | URY | 2011 | 3.361637e+06 |
| 2826 | Uruguay | URY | 2010 | 3.352651e+06 |
| 2827 | Uzbekistan | UZB | 2020 | 3.423205e+07 |
| 2828 | Uzbekistan | UZB | 2019 | 3.358035e+07 |
| 2829 | Uzbekistan | UZB | 2018 | 3.295610e+07 |
| 2830 | Uzbekistan | UZB | 2017 | 3.238860e+07 |
| 2831 | Uzbekistan | UZB | 2016 | 3.184790e+07 |
| 2832 | Uzbekistan | UZB | 2015 | 3.129890e+07 |
| 2833 | Uzbekistan | UZB | 2014 | 3.075770e+07 |
| 2834 | Uzbekistan | UZB | 2013 | 3.024320e+07 |
| 2835 | Uzbekistan | UZB | 2012 | 2.977450e+07 |
| 2836 | Uzbekistan | UZB | 2011 | 2.933940e+07 |
| 2837 | Uzbekistan | UZB | 2010 | 2.856240e+07 |
| 2838 | Vanuatu | VUT | 2020 | 3.116850e+05 |
| 2839 | Vanuatu | VUT | 2019 | 3.044040e+05 |
| 2840 | Vanuatu | VUT | 2018 | 2.972980e+05 |
| 2841 | Vanuatu | VUT | 2017 | 2.902390e+05 |
| 2842 | Vanuatu | VUT | 2016 | 2.832180e+05 |
| 2843 | Vanuatu | VUT | 2015 | 2.764380e+05 |
| 2844 | Vanuatu | VUT | 2014 | 2.699270e+05 |
| 2845 | Vanuatu | VUT | 2013 | 2.635340e+05 |
| 2846 | Vanuatu | VUT | 2012 | 2.573130e+05 |
| 2847 | Vanuatu | VUT | 2011 | 2.512940e+05 |
| 2848 | Vanuatu | VUT | 2010 | 2.454530e+05 |
| 2849 | Venezuela, RB | VEN | 2020 | 2.849045e+07 |
| 2850 | Venezuela, RB | VEN | 2019 | 2.897168e+07 |
| 2851 | Venezuela, RB | VEN | 2018 | 2.982565e+07 |
| 2852 | Venezuela, RB | VEN | 2017 | 3.056343e+07 |
| 2853 | Venezuela, RB | VEN | 2016 | 3.074146e+07 |
| 2854 | Venezuela, RB | VEN | 2015 | 3.052972e+07 |
| 2855 | Venezuela, RB | VEN | 2014 | 3.019326e+07 |
| 2856 | Venezuela, RB | VEN | 2013 | 2.983802e+07 |
| 2857 | Venezuela, RB | VEN | 2012 | 2.947043e+07 |
| 2858 | Venezuela, RB | VEN | 2011 | 2.909616e+07 |
| 2859 | Venezuela, RB | VEN | 2010 | 2.871502e+07 |
| 2860 | Viet Nam | VNM | 2020 | 9.664868e+07 |
| 2861 | Viet Nam | VNM | 2019 | 9.577672e+07 |
| 2862 | Viet Nam | VNM | 2018 | 9.491433e+07 |
| 2863 | Viet Nam | VNM | 2017 | 9.403305e+07 |
| 2864 | Viet Nam | VNM | 2016 | 9.312653e+07 |
| 2865 | Viet Nam | VNM | 2015 | 9.219140e+07 |
| 2866 | Viet Nam | VNM | 2014 | 9.123550e+07 |
| 2867 | Viet Nam | VNM | 2013 | 9.026774e+07 |
| 2868 | Viet Nam | VNM | 2012 | 8.930133e+07 |
| 2869 | Viet Nam | VNM | 2011 | 8.834912e+07 |
| 2870 | Viet Nam | VNM | 2010 | 8.741101e+07 |
| 2871 | Virgin Islands (U.S.) | VIR | 2020 | 1.062900e+05 |
| 2872 | Virgin Islands (U.S.) | VIR | 2019 | 1.066690e+05 |
| 2873 | Virgin Islands (U.S.) | VIR | 2018 | 1.070010e+05 |
| 2874 | Virgin Islands (U.S.) | VIR | 2017 | 1.072810e+05 |
| 2875 | Virgin Islands (U.S.) | VIR | 2016 | 1.075160e+05 |
| 2876 | Virgin Islands (U.S.) | VIR | 2015 | 1.077120e+05 |
| 2877 | Virgin Islands (U.S.) | VIR | 2014 | 1.078820e+05 |
| 2878 | Virgin Islands (U.S.) | VIR | 2013 | 1.080410e+05 |
| 2879 | Virgin Islands (U.S.) | VIR | 2012 | 1.081880e+05 |
| 2880 | Virgin Islands (U.S.) | VIR | 2011 | 1.082900e+05 |
| 2881 | Virgin Islands (U.S.) | VIR | 2010 | 1.083570e+05 |
| 2882 | West Bank and Gaza | PSE | 2020 | 4.803269e+06 |
| 2883 | West Bank and Gaza | PSE | 2019 | 4.685306e+06 |
| 2884 | West Bank and Gaza | PSE | 2018 | 4.569087e+06 |
| 2885 | West Bank and Gaza | PSE | 2017 | 4.454805e+06 |
| 2886 | West Bank and Gaza | PSE | 2016 | 4.367088e+06 |
| 2887 | West Bank and Gaza | PSE | 2015 | 4.270092e+06 |
| 2888 | West Bank and Gaza | PSE | 2014 | 4.173398e+06 |
| 2889 | West Bank and Gaza | PSE | 2013 | 4.076708e+06 |
| 2890 | West Bank and Gaza | PSE | 2012 | 3.979998e+06 |
| 2891 | West Bank and Gaza | PSE | 2011 | 3.882986e+06 |
| 2892 | West Bank and Gaza | PSE | 2010 | 3.786161e+06 |
| 2893 | Yemen, Rep. | YEM | 2020 | 3.228405e+07 |
| 2894 | Yemen, Rep. | YEM | 2019 | 3.154669e+07 |
| 2895 | Yemen, Rep. | YEM | 2018 | 3.079051e+07 |
| 2896 | Yemen, Rep. | YEM | 2017 | 3.003439e+07 |
| 2897 | Yemen, Rep. | YEM | 2016 | 2.927400e+07 |
| 2898 | Yemen, Rep. | YEM | 2015 | 2.851654e+07 |
| 2899 | Yemen, Rep. | YEM | 2014 | 2.775330e+07 |
| 2900 | Yemen, Rep. | YEM | 2013 | 2.698400e+07 |
| 2901 | Yemen, Rep. | YEM | 2012 | 2.622339e+07 |
| 2902 | Yemen, Rep. | YEM | 2011 | 2.547561e+07 |
| 2903 | Yemen, Rep. | YEM | 2010 | 2.474395e+07 |
| 2904 | Zambia | ZMB | 2020 | 1.892772e+07 |
| 2905 | Zambia | ZMB | 2019 | 1.838048e+07 |
| 2906 | Zambia | ZMB | 2018 | 1.783589e+07 |
| 2907 | Zambia | ZMB | 2017 | 1.729805e+07 |
| 2908 | Zambia | ZMB | 2016 | 1.676776e+07 |
| 2909 | Zambia | ZMB | 2015 | 1.624823e+07 |
| 2910 | Zambia | ZMB | 2014 | 1.573779e+07 |
| 2911 | Zambia | ZMB | 2013 | 1.523498e+07 |
| 2912 | Zambia | ZMB | 2012 | 1.474466e+07 |
| 2913 | Zambia | ZMB | 2011 | 1.426581e+07 |
| 2914 | Zambia | ZMB | 2010 | 1.379209e+07 |
| 2915 | Zimbabwe | ZWE | 2020 | 1.566967e+07 |
| 2916 | Zimbabwe | ZWE | 2019 | 1.535461e+07 |
| 2917 | Zimbabwe | ZWE | 2018 | 1.505218e+07 |
| 2918 | Zimbabwe | ZWE | 2017 | 1.475110e+07 |
| 2919 | Zimbabwe | ZWE | 2016 | 1.445270e+07 |
| 2920 | Zimbabwe | ZWE | 2015 | 1.415494e+07 |
| 2921 | Zimbabwe | ZWE | 2014 | 1.385575e+07 |
| 2922 | Zimbabwe | ZWE | 2013 | 1.355542e+07 |
| 2923 | Zimbabwe | ZWE | 2012 | 1.326533e+07 |
| 2924 | Zimbabwe | ZWE | 2011 | 1.302578e+07 |
| 2925 | Zimbabwe | ZWE | 2010 | 1.283977e+07 |
worldbank_population = pd.DataFrame(worldbank_population)
excel_worldbank_population = "worldbank_population.xlsx"
worldbank_population.to_excel(excel_worldbank_population, index=False)
url = "https://happiness-report.s3.amazonaws.com/2021/DataPanelWHR2021C2.xls"
happiness = pd.read_excel(url)
pd.set_option('display.max_rows', None)
print(happiness )
Country name year Life Ladder Log GDP per capita \
0 Afghanistan 2008 3.723590 7.370100
1 Afghanistan 2009 4.401778 7.539972
2 Afghanistan 2010 4.758381 7.646709
3 Afghanistan 2011 3.831719 7.619532
4 Afghanistan 2012 3.782938 7.705479
5 Afghanistan 2013 3.572100 7.725029
6 Afghanistan 2014 3.130896 7.718354
7 Afghanistan 2015 3.982855 7.701992
8 Afghanistan 2016 4.220169 7.696560
9 Afghanistan 2017 2.661718 7.697381
10 Afghanistan 2018 2.694303 7.691767
11 Afghanistan 2019 2.375092 7.697248
12 Albania 2007 4.634252 9.142183
13 Albania 2009 5.485470 9.261868
14 Albania 2010 5.268937 9.303230
15 Albania 2011 5.867422 9.331056
16 Albania 2012 5.510124 9.346783
17 Albania 2013 4.550648 9.358584
18 Albania 2014 4.813763 9.378244
19 Albania 2015 4.606651 9.403102
20 Albania 2016 4.511101 9.437311
21 Albania 2017 4.639548 9.475548
22 Albania 2018 5.004403 9.517920
23 Albania 2019 4.995318 9.544080
24 Albania 2020 5.364910 9.497252
25 Algeria 2010 5.463567 9.286936
26 Algeria 2011 5.317194 9.296691
27 Algeria 2012 5.604596 9.310611
28 Algeria 2014 6.354898 9.335159
29 Algeria 2016 5.340854 9.362022
30 Algeria 2017 5.248912 9.354488
31 Algeria 2018 5.043086 9.348318
32 Algeria 2019 4.744627 9.336946
33 Angola 2011 5.589001 8.945782
34 Angola 2012 4.360250 8.991773
35 Angola 2013 3.937107 9.004611
36 Angola 2014 3.794838 9.016735
37 Argentina 2006 6.312925 9.941642
38 Argentina 2007 6.073158 10.017901
39 Argentina 2008 5.961034 10.047747
40 Argentina 2009 6.424133 9.976742
41 Argentina 2010 6.441067 10.065669
42 Argentina 2011 6.775805 10.112445
43 Argentina 2012 6.468387 10.090758
44 Argentina 2013 6.582260 10.103335
45 Argentina 2014 6.671114 10.066894
46 Argentina 2015 6.697131 10.083059
47 Argentina 2016 6.427221 10.051465
48 Argentina 2017 6.039330 10.067430
49 Argentina 2018 5.792797 10.032141
50 Argentina 2019 6.085561 10.000340
51 Argentina 2020 5.900567 9.850450
52 Armenia 2006 4.289311 9.043633
53 Armenia 2007 4.881516 9.180747
54 Armenia 2008 4.651972 9.256032
55 Armenia 2009 4.177582 9.110784
56 Armenia 2010 4.367811 9.136283
57 Armenia 2011 4.260491 9.182483
58 Armenia 2012 4.319712 9.249339
59 Armenia 2013 4.277191 9.277186
60 Armenia 2014 4.453083 9.307452
61 Armenia 2015 4.348320 9.334446
62 Armenia 2016 4.325472 9.332829
63 Armenia 2017 4.287736 9.402205
64 Armenia 2018 5.062449 9.450535
65 Armenia 2019 5.488087 9.521770
66 Australia 2005 7.340688 10.658608
67 Australia 2007 7.285391 10.702894
68 Australia 2008 7.253757 10.718780
69 Australia 2010 7.450047 10.722262
70 Australia 2011 7.405616 10.732697
71 Australia 2012 7.195586 10.753672
72 Australia 2013 7.364169 10.761981
73 Australia 2014 7.288550 10.772080
74 Australia 2015 7.309061 10.779378
75 Australia 2016 7.250080 10.791088
76 Australia 2017 7.257038 10.797644
77 Australia 2018 7.176993 10.811262
78 Australia 2019 7.233995 10.814893
79 Australia 2020 7.137368 10.759864
80 Austria 2006 7.122211 10.841940
81 Austria 2008 7.180954 10.886662
82 Austria 2010 7.302679 10.861471
83 Austria 2011 7.470513 10.886909
84 Austria 2012 7.400689 10.889132
85 Austria 2013 7.498803 10.883492
86 Austria 2014 6.950000 10.882268
87 Austria 2015 7.076447 10.881152
88 Austria 2016 7.048072 10.890950
89 Austria 2017 7.293728 10.908466
90 Austria 2018 7.396002 10.927505
91 Austria 2019 7.195361 10.939381
92 Austria 2020 7.213489 10.851118
93 Azerbaijan 2006 4.727871 9.170049
94 Azerbaijan 2007 4.568160 9.385553
95 Azerbaijan 2008 4.817189 9.465227
96 Azerbaijan 2009 4.573725 9.534023
97 Azerbaijan 2010 4.218611 9.568907
98 Azerbaijan 2011 4.680470 9.540022
99 Azerbaijan 2012 4.910772 9.548524
100 Azerbaijan 2013 5.481178 9.592381
101 Azerbaijan 2014 5.251530 9.607490
102 Azerbaijan 2015 5.146775 9.606018
103 Azerbaijan 2016 5.303895 9.563725
104 Azerbaijan 2017 5.152279 9.555448
105 Azerbaijan 2018 5.167995 9.561677
106 Azerbaijan 2019 5.173389 9.575251
107 Bahrain 2009 5.700523 10.709387
108 Bahrain 2010 5.936869 10.705819
109 Bahrain 2011 4.823976 10.695849
110 Bahrain 2012 5.027187 10.715547
111 Bahrain 2013 6.689711 10.756761
112 Bahrain 2014 6.165134 10.783467
113 Bahrain 2015 6.007375 10.785271
114 Bahrain 2016 6.169673 10.780850
115 Bahrain 2017 6.227321 10.771480
116 Bahrain 2019 7.098012 10.714991
117 Bahrain 2020 6.173176 10.619904
118 Bangladesh 2006 4.318909 7.782841
119 Bangladesh 2007 4.607322 7.838781
120 Bangladesh 2008 5.052279 7.885724
121 Bangladesh 2009 5.082851 7.923776
122 Bangladesh 2010 4.858481 7.966749
123 Bangladesh 2011 4.985649 8.017946
124 Bangladesh 2012 4.724444 8.069572
125 Bangladesh 2013 4.660161 8.116403
126 Bangladesh 2014 4.635565 8.163822
127 Bangladesh 2015 4.633474 8.216118
128 Bangladesh 2016 4.556141 8.273924
129 Bangladesh 2017 4.309771 8.333532
130 Bangladesh 2018 4.499217 8.398730
131 Bangladesh 2019 5.114217 8.466684
132 Bangladesh 2020 5.279987 8.472195
133 Belarus 2006 5.657650 9.489099
134 Belarus 2007 5.616976 9.576188
135 Belarus 2008 5.463332 9.676768
136 Belarus 2009 5.564131 9.680996
137 Belarus 2010 5.525923 9.757792
138 Belarus 2011 5.225308 9.812018
139 Belarus 2012 5.749043 9.829665
140 Belarus 2013 5.876466 9.839491
141 Belarus 2014 5.812401 9.855708
142 Belarus 2015 5.718908 9.815067
143 Belarus 2016 5.177899 9.788223
144 Belarus 2017 5.552915 9.813574
145 Belarus 2018 5.233770 9.846136
146 Belarus 2019 5.821453 9.860039
147 Belgium 2005 7.262290 10.744605
148 Belgium 2007 7.218840 10.791979
149 Belgium 2008 7.116591 10.788538
150 Belgium 2010 6.853514 10.779181
151 Belgium 2011 7.111364 10.782974
152 Belgium 2012 6.935122 10.784138
153 Belgium 2013 7.103661 10.784006
154 Belgium 2014 6.855329 10.795229
155 Belgium 2015 6.904219 10.809559
156 Belgium 2016 6.948936 10.819170
157 Belgium 2017 6.928348 10.834178
158 Belgium 2018 6.892172 10.844393
159 Belgium 2019 6.772138 10.853364
160 Belgium 2020 6.838761 10.770537
161 Belize 2007 6.450644 8.892479
162 Belize 2014 5.955647 8.883127
163 Benin 2006 3.329802 7.865885
164 Benin 2008 3.667140 7.915053
165 Benin 2011 3.870280 7.903917
166 Benin 2012 3.193469 7.922932
167 Benin 2013 3.479413 7.964470
168 Benin 2014 3.347419 7.998286
169 Benin 2015 3.624664 7.988194
170 Benin 2016 4.007358 7.993432
171 Benin 2017 4.853181 8.021096
172 Benin 2018 5.819827 8.058573
173 Benin 2019 4.976361 8.097825
174 Benin 2020 4.407746 8.102292
175 Bhutan 2013 5.569092 9.122986
176 Bhutan 2014 4.938578 9.166805
177 Bhutan 2015 5.082129 9.218924
178 Bolivia 2006 5.373986 8.686212
179 Bolivia 2007 5.628419 8.713645
180 Bolivia 2008 5.297873 8.756404
181 Bolivia 2009 6.085579 8.772761
182 Bolivia 2010 5.780620 8.796763
183 Bolivia 2011 5.778874 8.831271
184 Bolivia 2012 6.018895 8.865225
185 Bolivia 2013 5.767429 8.915230
186 Bolivia 2014 5.864799 8.952947
187 Bolivia 2015 5.834329 8.985247
188 Bolivia 2016 5.769723 9.012200
189 Bolivia 2017 5.650553 9.038804
190 Bolivia 2018 5.915734 9.065954
191 Bolivia 2019 5.674271 9.073888
192 Bolivia 2020 5.559259 8.997990
193 Bosnia and Herzegovina 2007 4.899807 9.266820
194 Bosnia and Herzegovina 2009 4.963477 9.296339
195 Bosnia and Herzegovina 2010 4.668518 9.312170
196 Bosnia and Herzegovina 2011 4.994671 9.333239
197 Bosnia and Herzegovina 2012 4.773145 9.341687
198 Bosnia and Herzegovina 2013 5.123664 9.382378
199 Bosnia and Herzegovina 2014 5.248954 9.411018
200 Bosnia and Herzegovina 2015 5.117178 9.456696
201 Bosnia and Herzegovina 2016 5.180865 9.500314
202 Bosnia and Herzegovina 2017 5.089902 9.531589
203 Bosnia and Herzegovina 2018 5.887401 9.576346
204 Bosnia and Herzegovina 2019 6.015522 9.608767
205 Bosnia and Herzegovina 2020 5.515816 9.583344
206 Botswana 2006 4.739367 9.492278
207 Botswana 2008 5.451147 9.589868
208 Botswana 2010 3.553020 9.555798
209 Botswana 2011 3.519921 9.600382
210 Botswana 2012 4.835939 9.632069
211 Botswana 2013 4.128299 9.728311
212 Botswana 2014 4.031197 9.756402
213 Botswana 2015 3.761965 9.724023
214 Botswana 2016 3.498937 9.747831
215 Botswana 2017 3.504881 9.755754
216 Botswana 2018 3.461366 9.777593
217 Botswana 2019 3.471085 9.785069
218 Brazil 2005 6.636771 9.438417
219 Brazil 2007 6.320673 9.514919
220 Brazil 2008 6.691425 9.554664
221 Brazil 2009 7.000832 9.543785
222 Brazil 2010 6.837331 9.606989
223 Brazil 2011 7.037817 9.636804
224 Brazil 2012 6.660004 9.646898
225 Brazil 2013 7.140283 9.667768
226 Brazil 2014 6.980999 9.664237
227 Brazil 2015 6.546897 9.619746
228 Brazil 2016 6.374817 9.578201
229 Brazil 2017 6.332929 9.583272
230 Brazil 2018 6.190922 9.588520
231 Brazil 2019 6.451149 9.592306
232 Brazil 2020 6.109718 9.522141
233 Bulgaria 2007 3.843798 9.715486
234 Bulgaria 2010 3.912276 9.765453
235 Bulgaria 2011 3.875382 9.795103
236 Bulgaria 2012 4.222297 9.804495
237 Bulgaria 2013 3.993021 9.813273
238 Bulgaria 2014 4.438440 9.837726
239 Bulgaria 2015 4.865401 9.883226
240 Bulgaria 2016 4.837561 9.927648
241 Bulgaria 2017 5.096902 9.969418
242 Bulgaria 2018 5.098814 10.007013
243 Bulgaria 2019 5.108438 10.047213
244 Bulgaria 2020 5.597723 9.990658
245 Burkina Faso 2006 3.801491 7.366805
246 Burkina Faso 2007 4.017130 7.376977
247 Burkina Faso 2008 3.846439 7.403108
248 Burkina Faso 2010 4.035561 7.452925
249 Burkina Faso 2011 4.785367 7.486960
250 Burkina Faso 2012 3.955008 7.519517
251 Burkina Faso 2013 3.325950 7.546011
252 Burkina Faso 2014 3.481348 7.558751
253 Burkina Faso 2015 4.418930 7.567736
254 Burkina Faso 2016 4.205635 7.596462
255 Burkina Faso 2017 4.646891 7.627303
256 Burkina Faso 2018 4.927236 7.664604
257 Burkina Faso 2019 4.740893 7.691488
258 Burundi 2008 3.563228 6.718762
259 Burundi 2009 3.791681 6.723309
260 Burundi 2011 3.705894 6.748176
261 Burundi 2014 2.904535 6.786983
262 Burundi 2018 3.775283 6.635322
263 Cambodia 2006 3.568745 7.746449
264 Cambodia 2007 4.155971 7.828794
265 Cambodia 2008 4.462164 7.878774
266 Cambodia 2009 4.110626 7.864644
267 Cambodia 2010 4.141072 7.907173
268 Cambodia 2011 4.161225 7.959593
269 Cambodia 2012 3.898707 8.013871
270 Cambodia 2013 3.674467 8.068359
271 Cambodia 2014 3.883306 8.120969
272 Cambodia 2015 4.162165 8.172928
273 Cambodia 2016 4.461259 8.225224
274 Cambodia 2017 4.585842 8.275981
275 Cambodia 2018 5.121838 8.333111
276 Cambodia 2019 4.998285 8.386811
277 Cambodia 2020 4.376985 8.361936
278 Cameroon 2006 3.851072 8.007079
279 Cameroon 2007 4.349939 8.027517
280 Cameroon 2008 4.291800 8.034303
281 Cameroon 2009 4.741408 8.028528
282 Cameroon 2010 4.554257 8.034702
283 Cameroon 2011 4.433885 8.047761
284 Cameroon 2012 4.244634 8.064879
285 Cameroon 2013 4.271038 8.090330
286 Cameroon 2014 4.240441 8.120489
287 Cameroon 2015 5.037965 8.148646
288 Cameroon 2016 4.816232 8.167479
289 Cameroon 2017 5.074051 8.175977
290 Cameroon 2018 5.250738 8.189674
291 Cameroon 2019 4.936738 8.203218
292 Cameroon 2020 5.241078 8.174634
293 Canada 2005 7.418048 10.651751
294 Canada 2007 7.481753 10.739180
295 Canada 2008 7.485604 10.738377
296 Canada 2009 7.487824 10.697238
297 Canada 2010 7.650346 10.716547
298 Canada 2011 7.426054 10.737743
299 Canada 2012 7.415144 10.744354
300 Canada 2013 7.593794 10.756812
301 Canada 2014 7.304258 10.775055
302 Canada 2015 7.412773 10.774161
303 Canada 2016 7.244846 10.772802
304 Canada 2017 7.414868 10.792074
305 Canada 2018 7.175497 10.798032
306 Canada 2019 7.109076 10.800216
307 Canada 2020 7.024905 10.729514
308 Central African Republic 2007 4.160130 6.987199
309 Central African Republic 2010 3.567893 7.091202
310 Central African Republic 2011 3.677826 7.125054
311 Central African Republic 2016 2.693061 6.785016
312 Central African Republic 2017 3.475862 6.816519
313 Chad 2006 3.434801 7.360411
314 Chad 2007 4.141327 7.358672
315 Chad 2008 4.632468 7.355508
316 Chad 2009 3.639445 7.363704
317 Chad 2010 3.742871 7.457431
318 Chad 2011 4.393482 7.424624
319 Chad 2012 4.032975 7.476016
320 Chad 2013 3.507663 7.497941
321 Chad 2014 3.460183 7.531695
322 Chad 2015 4.322675 7.526775
323 Chad 2016 4.029350 7.430738
324 Chad 2017 4.558937 7.369620
325 Chad 2018 4.486325 7.362847
326 Chad 2019 4.250799 7.364944
327 Chile 2006 6.062852 9.849908
328 Chile 2007 5.697930 9.887110
329 Chile 2008 5.789439 9.911082
330 Chile 2009 6.493686 9.884724
331 Chile 2010 6.635656 9.931132
332 Chile 2011 6.526335 9.980473
333 Chile 2012 6.599129 10.022662
334 Chile 2013 6.740154 10.052527
335 Chile 2014 6.844238 10.059429
336 Chile 2015 6.532750 10.070428
337 Chile 2016 6.579056 10.074142
338 Chile 2017 6.320119 10.071705
339 Chile 2018 6.436221 10.096529
340 Chile 2019 5.942250 10.095188
341 Chile 2020 6.150643 10.020142
342 China 2006 4.560495 8.696120
343 China 2007 4.862862 8.823954
344 China 2008 4.846295 8.910992
345 China 2009 4.454361 8.995857
346 China 2010 4.652737 9.092104
347 China 2011 5.037208 9.178532
348 China 2012 5.094917 9.249320
349 China 2013 5.241090 9.319200
350 China 2014 5.195619 9.385755
351 China 2015 5.303878 9.448723
352 China 2016 5.324956 9.509552
353 China 2017 5.099061 9.571116
354 China 2018 5.131434 9.631892
355 China 2019 5.144120 9.687612
356 China 2020 5.771065 9.701755
357 Colombia 2006 6.024943 9.277375
358 Colombia 2007 6.138412 9.330238
359 Colombia 2008 6.168395 9.350784
360 Colombia 2009 6.271605 9.350991
361 Colombia 2010 6.408113 9.384451
362 Colombia 2011 6.463953 9.441931
363 Colombia 2012 6.374880 9.471291
364 Colombia 2013 6.606551 9.512274
365 Colombia 2014 6.448789 9.546183
366 Colombia 2015 6.387572 9.563641
367 Colombia 2016 6.233715 9.570699
368 Colombia 2017 6.157342 9.569167
369 Colombia 2018 5.983512 9.578836
370 Colombia 2019 6.350298 9.597702
371 Colombia 2020 5.709175 9.495491
372 Comoros 2009 3.476027 7.951781
373 Comoros 2010 3.812191 7.964951
374 Comoros 2011 3.838486 7.980955
375 Comoros 2012 3.955640 7.988264
376 Comoros 2018 3.972820 8.028402
377 Comoros 2019 4.608616 8.033134
378 Congo (Brazzaville) 2008 3.819792 8.082047
379 Congo (Brazzaville) 2011 4.509824 8.180340
380 Congo (Brazzaville) 2012 3.919342 8.191727
381 Congo (Brazzaville) 2013 3.954951 8.200904
382 Congo (Brazzaville) 2014 4.056013 8.242097
383 Congo (Brazzaville) 2015 4.690830 8.243382
384 Congo (Brazzaville) 2016 4.119493 8.189586
385 Congo (Brazzaville) 2017 4.883991 8.145705
386 Congo (Brazzaville) 2018 5.490214 8.135762
387 Congo (Brazzaville) 2019 5.212623 8.101092
388 Congo (Kinshasa) 2009 3.983849 6.728164
389 Congo (Kinshasa) 2011 4.516964 6.796630
390 Congo (Kinshasa) 2012 4.639227 6.831725
391 Congo (Kinshasa) 2013 4.497477 6.879825
392 Congo (Kinshasa) 2014 4.414300 6.937111
393 Congo (Kinshasa) 2015 3.902742 6.970958
394 Congo (Kinshasa) 2016 4.521935 6.961839
395 Congo (Kinshasa) 2017 4.311033 6.965846
396 Costa Rica 2006 7.082465 9.564669
397 Costa Rica 2007 7.432132 9.629647
398 Costa Rica 2008 6.850680 9.661901
399 Costa Rica 2009 7.614929 9.639322
400 Costa Rica 2010 7.271054 9.675203
401 Costa Rica 2011 7.228889 9.705276
402 Costa Rica 2012 7.272250 9.740347
403 Costa Rica 2013 7.158000 9.751308
404 Costa Rica 2014 7.247086 9.774683
405 Costa Rica 2015 6.854004 9.799487
406 Costa Rica 2016 7.135618 9.830494
407 Costa Rica 2017 7.225182 9.858093
408 Costa Rica 2018 7.141075 9.874401
409 Costa Rica 2019 6.997619 9.885447
410 Croatia 2007 5.820908 10.161589
411 Croatia 2009 5.433320 10.103759
412 Croatia 2010 5.595575 10.090949
413 Croatia 2011 5.385373 10.091299
414 Croatia 2012 6.027635 10.071725
415 Croatia 2013 5.885463 10.069010
416 Croatia 2014 5.380692 10.072043
417 Croatia 2015 5.205438 10.104363
418 Croatia 2016 5.416875 10.145592
419 Croatia 2017 5.343166 10.188506
420 Croatia 2018 5.536271 10.224031
421 Croatia 2019 5.625744 10.257958
422 Croatia 2020 6.507992 10.165817
423 Cuba 2006 5.417869 NaN
424 Cyprus 2006 6.237958 10.565565
425 Cyprus 2009 6.833477 10.557503
426 Cyprus 2010 6.386546 10.551297
427 Cyprus 2011 6.689609 10.529789
428 Cyprus 2012 6.180507 10.479476
429 Cyprus 2013 5.438952 10.414024
430 Cyprus 2014 5.627124 10.406218
431 Cyprus 2015 5.439161 10.445101
432 Cyprus 2016 5.794619 10.505802
433 Cyprus 2017 6.062051 10.539188
434 Cyprus 2018 6.276443 10.566755
435 Cyprus 2019 6.136833 10.585187
436 Cyprus 2020 6.259810 NaN
437 Czech Republic 2005 6.439257 10.324370
438 Czech Republic 2007 6.500194 10.436629
439 Czech Republic 2010 6.249618 10.419456
440 Czech Republic 2011 6.331491 10.435011
441 Czech Republic 2012 6.334149 10.425581
442 Czech Republic 2013 6.697656 10.420401
443 Czech Republic 2014 6.483730 10.446137
444 Czech Republic 2015 6.608017 10.495902
445 Czech Republic 2016 6.735627 10.518191
446 Czech Republic 2017 6.789568 10.558141
447 Czech Republic 2018 7.034165 10.582860
448 Czech Republic 2020 6.897091 10.530134
449 Denmark 2005 8.018934 10.851397
450 Denmark 2007 7.834233 10.891111
451 Denmark 2008 7.970892 10.880102
452 Denmark 2009 7.683359 10.824442
453 Denmark 2010 7.770515 10.838536
454 Denmark 2011 7.788232 10.847698
455 Denmark 2012 7.519909 10.846198
456 Denmark 2013 7.588607 10.851319
457 Denmark 2014 7.507559 10.862313
458 Denmark 2015 7.514425 10.878405
459 Denmark 2016 7.557783 10.902544
460 Denmark 2017 7.593702 10.916268
461 Denmark 2018 7.648786 10.934941
462 Denmark 2019 7.693003 10.954033
463 Denmark 2020 7.514631 10.909995
464 Djibouti 2008 5.009330 8.111199
465 Djibouti 2009 4.905925 7.926556
466 Djibouti 2010 5.005811 7.811863
467 Djibouti 2011 4.369194 7.880099
468 Dominican Republic 2006 5.087968 9.313571
469 Dominican Republic 2007 5.081306 9.372158
470 Dominican Republic 2008 4.842306 9.391065
471 Dominican Republic 2009 5.431614 9.388014
472 Dominican Republic 2010 4.735021 9.455829
473 Dominican Republic 2011 5.396535 9.474575
474 Dominican Republic 2012 4.753311 9.489464
475 Dominican Republic 2013 5.015515 9.525321
476 Dominican Republic 2014 5.387332 9.581879
477 Dominican Republic 2015 5.061862 9.637460
478 Dominican Republic 2016 5.238698 9.690702
479 Dominican Republic 2017 5.605203 9.725278
480 Dominican Republic 2018 5.433216 9.781984
481 Dominican Republic 2019 6.004237 9.821140
482 Dominican Republic 2020 5.168410 9.802446
483 Ecuador 2006 5.024191 9.185779
484 Ecuador 2007 4.995875 9.190714
485 Ecuador 2008 5.296513 9.235755
486 Ecuador 2009 6.021803 9.225117
487 Ecuador 2010 5.838051 9.243869
488 Ecuador 2011 5.795088 9.304221
489 Ecuador 2012 5.960716 9.344117
490 Ecuador 2013 6.019206 9.377429
491 Ecuador 2014 5.945852 9.399179
492 Ecuador 2015 5.964075 9.383989
493 Ecuador 2016 6.115438 9.354581
494 Ecuador 2017 5.839519 9.360303
495 Ecuador 2018 6.128010 9.355457
496 Ecuador 2019 5.809131 9.339202
497 Ecuador 2020 5.354462 9.243865
498 Egypt 2005 5.167754 9.035634
499 Egypt 2007 5.540511 9.135076
500 Egypt 2008 4.631741 9.186407
501 Egypt 2009 5.066164 9.213439
502 Egypt 2010 4.668916 9.243782
503 Egypt 2011 4.174159 9.240136
504 Egypt 2012 4.204157 9.240006
505 Egypt 2013 3.558520 9.238947
506 Egypt 2014 4.885073 9.245096
507 Egypt 2015 4.762538 9.265818
508 Egypt 2016 4.556741 9.286913
509 Egypt 2017 3.929344 9.306967
510 Egypt 2018 4.005451 9.338411
511 Egypt 2019 4.327832 9.372736
512 Egypt 2020 4.472397 9.382727
513 El Salvador 2006 5.700930 8.873026
514 El Salvador 2007 5.295535 8.887126
515 El Salvador 2008 5.191494 8.908267
516 El Salvador 2009 6.839087 8.882967
517 El Salvador 2010 6.739911 8.899548
518 El Salvador 2011 4.741295 8.932700
519 El Salvador 2012 5.934371 8.956071
520 El Salvador 2013 6.325063 8.973660
521 El Salvador 2014 5.856524 8.986002
522 El Salvador 2015 6.018496 9.004916
523 El Salvador 2016 6.139825 9.025170
524 El Salvador 2017 6.339318 9.042402
525 El Salvador 2018 6.241199 9.061327
526 El Salvador 2019 6.454821 9.079775
527 El Salvador 2020 5.461927 9.018846
528 Estonia 2006 5.371055 10.269773
529 Estonia 2007 5.332044 10.347340
530 Estonia 2008 5.451938 10.297791
531 Estonia 2009 5.137739 10.143838
532 Estonia 2011 5.486820 10.247500
533 Estonia 2012 5.363928 10.281851
534 Estonia 2013 5.367446 10.298781
535 Estonia 2014 5.555983 10.330840
536 Estonia 2015 5.628909 10.348465
537 Estonia 2016 5.649675 10.374149
538 Estonia 2017 5.938396 10.428835
539 Estonia 2018 6.091302 10.471868
540 Estonia 2019 6.034641 10.510816
541 Estonia 2020 6.452564 10.458589
542 Ethiopia 2012 4.561169 7.270575
543 Ethiopia 2013 4.444827 7.342895
544 Ethiopia 2014 4.506647 7.412543
545 Ethiopia 2015 4.573155 7.483854
546 Ethiopia 2016 4.297849 7.546919
547 Ethiopia 2017 4.180315 7.611625
548 Ethiopia 2018 4.379262 7.651364
549 Ethiopia 2019 4.099555 7.705131
550 Ethiopia 2020 4.549220 7.710983
551 Finland 2006 7.672449 10.745330
552 Finland 2008 7.670627 10.795864
553 Finland 2010 7.393264 10.733676
554 Finland 2011 7.354225 10.754196
555 Finland 2012 7.420209 10.735366
556 Finland 2013 7.444636 10.721698
557 Finland 2014 7.384571 10.713906
558 Finland 2015 7.447926 10.716033
559 Finland 2016 7.659843 10.739903
560 Finland 2017 7.788252 10.768089
561 Finland 2018 7.858107 10.782932
562 Finland 2019 7.780348 10.791813
563 Finland 2020 7.889350 10.750446
564 France 2005 7.093393 10.641690
565 France 2006 6.582700 10.658916
566 France 2008 7.008065 10.673645
567 France 2009 6.283498 10.639346
568 France 2010 6.797901 10.653713
569 France 2011 6.959185 10.670567
570 France 2012 6.649365 10.668853
571 France 2013 6.667121 10.669452
572 France 2014 6.466868 10.674232
573 France 2015 6.357625 10.681743
574 France 2016 6.475209 10.690000
575 France 2017 6.635222 10.710555
576 France 2018 6.665904 10.726808
577 France 2019 6.689644 10.740378
578 France 2020 6.714112 10.643280
579 Gabon 2011 4.255401 9.607934
580 Gabon 2012 3.972059 9.621227
581 Gabon 2013 3.800287 9.638289
582 Gabon 2014 3.918073 9.644469
583 Gabon 2015 4.661013 9.649174
584 Gabon 2016 4.831764 9.639439
585 Gabon 2017 4.782383 9.616257
586 Gabon 2018 4.783009 9.598550
587 Gabon 2019 4.914393 9.607087
588 Gambia 2017 4.117939 7.636584
589 Gambia 2018 4.922099 7.670534
590 Gambia 2019 5.163627 7.699350
591 Georgia 2006 3.675108 8.993416
592 Georgia 2007 3.707195 9.117117
593 Georgia 2008 4.156090 9.144053
594 Georgia 2009 3.800639 9.115746
595 Georgia 2010 4.101837 9.183661
596 Georgia 2011 4.203031 9.263072
597 Georgia 2012 4.254446 9.332182
598 Georgia 2013 4.348921 9.370765
599 Georgia 2014 4.287508 9.413660
600 Georgia 2015 4.121941 9.441860
601 Georgia 2016 4.448386 9.469912
602 Georgia 2017 4.450775 9.517068
603 Georgia 2018 4.659097 9.565009
604 Georgia 2019 4.891836 9.616757
605 Georgia 2020 5.123143 9.569304
606 Germany 2005 6.619550 10.689224
607 Germany 2007 6.416820 10.758531
608 Germany 2008 6.521790 10.770008
609 Germany 2009 6.641493 10.713883
610 Germany 2010 6.724531 10.756355
611 Germany 2011 6.621312 10.813384
612 Germany 2012 6.702362 10.815693
613 Germany 2013 6.965125 10.817237
614 Germany 2014 6.984214 10.835081
615 Germany 2015 7.037138 10.843672
616 Germany 2016 6.873763 10.857656
617 Germany 2017 7.074325 10.878269
618 Germany 2018 7.118364 10.890423
619 Germany 2019 7.035472 10.893314
620 Germany 2020 7.311898 10.833499
621 Ghana 2006 4.535020 8.073256
622 Ghana 2007 5.220148 8.090007
623 Ghana 2008 4.965135 8.151771
624 Ghana 2009 4.197696 8.173640
625 Ghana 2010 4.606252 8.224802
626 Ghana 2011 5.608200 8.332000
627 Ghana 2012 5.057262 8.397165
628 Ghana 2013 4.965053 8.444502
629 Ghana 2014 3.860351 8.450147
630 Ghana 2015 3.985916 8.449007
631 Ghana 2016 4.514411 8.460438
632 Ghana 2017 5.481311 8.516521
633 Ghana 2018 5.003693 8.555344
634 Ghana 2019 4.966810 8.596490
635 Ghana 2020 5.319483 8.589605
636 Greece 2005 6.006310 10.461699
637 Greece 2007 6.646961 10.543345
638 Greece 2009 6.038575 10.490745
639 Greece 2010 5.839559 10.433106
640 Greece 2011 5.372040 10.338819
641 Greece 2012 5.096354 10.268419
642 Greece 2013 4.720251 10.242719
643 Greece 2014 4.756237 10.256751
644 Greece 2015 5.622519 10.258951
645 Greece 2016 5.302619 10.261199
646 Greece 2017 5.148242 10.278116
647 Greece 2018 5.409289 10.299304
648 Greece 2019 5.952157 10.319384
649 Greece 2020 5.787616 10.214580
650 Guatemala 2006 5.901429 8.849806
651 Guatemala 2007 6.329581 8.891179
652 Guatemala 2008 6.414495 8.904189
653 Guatemala 2009 6.451916 8.890625
654 Guatemala 2010 6.289749 8.900550
655 Guatemala 2011 5.743354 8.923133
656 Guatemala 2012 5.855717 8.934624
657 Guatemala 2013 5.984601 8.953361
658 Guatemala 2014 6.536031 8.979554
659 Guatemala 2015 6.464987 9.002746
660 Guatemala 2016 6.358916 9.012591
661 Guatemala 2017 6.325119 9.026101
662 Guatemala 2018 6.626592 9.041739
663 Guatemala 2019 6.262175 9.063875
664 Guinea 2011 4.044569 7.567404
665 Guinea 2012 3.651555 7.602896
666 Guinea 2013 3.901793 7.619241
667 Guinea 2014 3.412483 7.632116
668 Guinea 2015 3.504694 7.644764
669 Guinea 2016 3.602855 7.721042
670 Guinea 2017 4.873723 7.791771
671 Guinea 2018 5.252227 7.823416
672 Guinea 2019 4.767684 7.849340
673 Guyana 2007 5.992826 8.773289
674 Haiti 2006 3.754156 7.407168
675 Haiti 2008 3.846329 7.416673
676 Haiti 2010 3.765999 7.384417
677 Haiti 2011 4.844574 7.423120
678 Haiti 2012 4.413475 7.436831
679 Haiti 2013 4.621962 7.463928
680 Haiti 2014 3.888778 7.477151
681 Haiti 2015 3.569762 7.475525
682 Haiti 2016 3.352300 7.476534
683 Haiti 2017 3.823866 7.475148
684 Haiti 2018 3.614928 7.477138
685 Honduras 2006 5.396520 8.462430
686 Honduras 2007 5.097154 8.499909
687 Honduras 2008 5.420331 8.519512
688 Honduras 2009 6.033189 8.473840
689 Honduras 2010 5.866131 8.490228
690 Honduras 2011 4.961031 8.508435
691 Honduras 2012 4.602218 8.530200
692 Honduras 2013 4.713358 8.539632
693 Honduras 2014 5.055726 8.552060
694 Honduras 2015 4.845437 8.572327
695 Honduras 2016 5.648155 8.593342
696 Honduras 2017 6.019986 8.623713
697 Honduras 2018 5.908424 8.643342
698 Honduras 2019 5.930051 8.653117
699 Hong Kong S.A.R. of China 2006 5.511187 10.746425
700 Hong Kong S.A.R. of China 2008 5.137262 10.815545
701 Hong Kong S.A.R. of China 2009 5.397056 10.788494
702 Hong Kong S.A.R. of China 2010 5.642835 10.846634
703 Hong Kong S.A.R. of China 2011 5.474011 10.886932
704 Hong Kong S.A.R. of China 2012 5.483765 10.892753
705 Hong Kong S.A.R. of China 2014 5.458051 10.939503
706 Hong Kong S.A.R. of China 2016 5.498421 10.969857
707 Hong Kong S.A.R. of China 2017 5.362475 10.999584
708 Hong Kong S.A.R. of China 2019 5.659317 11.000313
709 Hong Kong S.A.R. of China 2020 5.295341 NaN
710 Hungary 2005 5.193933 10.107747
711 Hungary 2007 4.953917 10.152791
712 Hungary 2009 4.894600 10.097274
713 Hungary 2010 4.725132 10.106154
714 Hungary 2011 4.917603 10.127015
715 Hungary 2012 4.683358 10.117352
716 Hungary 2013 4.914467 10.139545
717 Hungary 2014 5.180563 10.183334
718 Hungary 2015 5.344383 10.223448
719 Hungary 2016 5.448902 10.248160
720 Hungary 2017 6.065039 10.293139
721 Hungary 2018 5.935771 10.344091
722 Hungary 2019 6.000260 10.392768
723 Hungary 2020 6.038050 10.335148
724 Iceland 2008 6.888284 10.861430
725 Iceland 2012 7.590660 10.777463
726 Iceland 2013 7.501394 10.808511
727 Iceland 2015 7.498071 10.853975
728 Iceland 2016 7.510035 10.904262
729 Iceland 2017 7.476214 10.925262
730 Iceland 2019 7.532505 10.930854
731 Iceland 2020 7.575490 10.824201
732 India 2006 5.348259 8.145189
733 India 2007 5.026793 8.203913
734 India 2008 5.145833 8.219664
735 India 2009 4.521518 8.281240
736 India 2010 4.989277 8.349294
737 India 2011 4.634871 8.387494
738 India 2012 4.720147 8.428305
739 India 2013 4.427789 8.478379
740 India 2014 4.424379 8.538408
741 India 2015 4.342079 8.604168
742 India 2016 4.179177 8.672601
743 India 2017 4.046111 8.730042
744 India 2018 3.818069 8.779066
745 India 2019 3.248770 8.817933
746 India 2020 4.225281 8.702772
747 Indonesia 2006 4.946978 8.850008
748 Indonesia 2007 5.101214 8.898289
749 Indonesia 2008 4.815310 8.943453
750 Indonesia 2009 5.472361 8.975410
751 Indonesia 2010 5.457299 9.022411
752 Indonesia 2011 5.172608 9.068801
753 Indonesia 2012 5.367774 9.113834
754 Indonesia 2013 5.292238 9.154508
755 Indonesia 2014 5.597375 9.190253
756 Indonesia 2015 5.042800 9.225190
757 Indonesia 2016 5.136325 9.262097
758 Indonesia 2017 5.098402 9.299801
759 Indonesia 2018 5.340296 9.338868
760 Indonesia 2019 5.346513 9.376888
761 Iran 2005 5.308190 9.392513
762 Iran 2007 5.336371 9.497391
763 Iran 2008 5.128988 9.488964
764 Iran 2011 4.767507 9.547193
765 Iran 2012 4.608928 9.457778
766 Iran 2013 5.139579 9.443441
767 Iran 2014 4.682224 9.475666
768 Iran 2015 4.749956 9.449208
769 Iran 2016 4.652731 9.561364
770 Iran 2017 4.716783 9.584374
771 Iran 2018 4.278118 NaN
772 Iran 2019 5.006146 NaN
773 Iran 2020 4.864528 NaN
774 Iraq 2008 4.589845 9.063396
775 Iraq 2009 4.775317 9.076148
776 Iraq 2010 5.065462 9.112019
777 Iraq 2011 4.725366 9.152244
778 Iraq 2012 4.659509 9.245508
779 Iraq 2013 4.725017 9.279796
780 Iraq 2014 4.541502 9.249623
781 Iraq 2015 4.493377 9.240935
782 Iraq 2016 4.412537 9.353771
783 Iraq 2017 4.462399 9.303099
784 Iraq 2018 4.886401 9.274262
785 Iraq 2020 4.785165 9.167186
786 Ireland 2006 7.144247 10.971882
787 Ireland 2008 7.568030 10.928620
788 Ireland 2009 7.045911 10.866337
789 Ireland 2010 7.257390 10.878826
790 Ireland 2011 7.006904 10.877893
791 Ireland 2012 6.964645 10.875911
792 Ireland 2013 6.760085 10.884071
793 Ireland 2014 7.018379 10.958863
794 Ireland 2015 6.830125 11.173858
795 Ireland 2016 7.040731 11.198688
796 Ireland 2017 7.060155 11.266106
797 Ireland 2018 6.962336 11.332250
798 Ireland 2019 7.254841 11.371147
799 Ireland 2020 7.034931 11.322803
800 Israel 2006 7.173417 10.389376
801 Israel 2007 6.841115 10.427745
802 Israel 2008 7.261261 10.439504
803 Israel 2009 7.352979 10.424802
804 Israel 2010 7.358916 10.461033
805 Israel 2011 7.433148 10.489279
806 Israel 2012 7.110855 10.493138
807 Israel 2013 7.320563 10.515121
808 Israel 2014 7.400570 10.532819
809 Israel 2015 7.079411 10.535648
810 Israel 2016 7.159011 10.555093
811 Israel 2017 7.331036 10.570462
812 Israel 2018 6.927179 10.585150
813 Israel 2019 7.331780 10.600675
814 Israel 2020 7.194928 10.538054
815 Italy 2005 6.853784 10.702738
816 Italy 2007 6.574412 10.727192
817 Italy 2008 6.779774 10.710900
818 Italy 2009 6.333800 10.652089
819 Italy 2010 6.354238 10.666001
820 Italy 2011 6.057086 10.671329
821 Italy 2012 5.839314 10.638372
822 Italy 2013 6.009374 10.608197
823 Italy 2014 6.026585 10.598977
824 Italy 2015 5.847684 10.607694
825 Italy 2016 5.954524 10.622244
826 Italy 2017 6.198870 10.640284
827 Italy 2018 6.516527 10.650134
828 Italy 2019 6.445417 10.655202
829 Italy 2020 6.488356 10.562572
830 Ivory Coast 2009 4.197182 8.208836
831 Ivory Coast 2013 3.739366 8.274495
832 Ivory Coast 2014 3.570369 8.333736
833 Ivory Coast 2015 4.445039 8.393250
834 Ivory Coast 2016 4.542546 8.437222
835 Ivory Coast 2017 5.037735 8.482758
836 Ivory Coast 2018 5.268375 8.522961
837 Ivory Coast 2019 5.392012 8.563745
838 Ivory Coast 2020 5.256504 8.564923
839 Jamaica 2006 6.207882 9.225333
840 Jamaica 2011 5.374446 9.163817
841 Jamaica 2013 5.708887 9.151133
842 Jamaica 2014 5.310539 9.152293
843 Jamaica 2017 5.889759 9.169349
844 Jamaica 2019 6.309239 9.186201
845 Japan 2005 6.515817 10.529193
846 Japan 2007 6.238198 10.557917
847 Japan 2008 5.910679 10.546437
848 Japan 2009 5.844999 10.490875
849 Japan 2010 6.056753 10.531758
850 Japan 2011 6.262794 10.532456
851 Japan 2012 5.968216 10.548893
852 Japan 2013 5.959362 10.570142
853 Japan 2014 5.922621 10.575209
854 Japan 2015 5.879684 10.588425
855 Japan 2016 5.954651 10.594784
856 Japan 2017 5.910676 10.617880
857 Japan 2018 5.793575 10.623133
858 Japan 2019 5.908039 10.631743
859 Japan 2020 6.117963 10.579548
860 Jordan 2005 6.294660 9.245755
861 Jordan 2007 5.598057 9.320656
862 Jordan 2008 4.930058 9.343456
863 Jordan 2009 5.999859 9.346684
864 Jordan 2010 5.569942 9.317488
865 Jordan 2011 5.539328 9.289198
866 Jordan 2012 5.131996 9.261048
867 Jordan 2013 5.171953 9.237214
868 Jordan 2014 5.333022 9.221872
869 Jordan 2015 5.404593 9.207395
870 Jordan 2016 5.271285 9.196954
871 Jordan 2017 4.808083 9.194330
872 Jordan 2018 4.638934 9.195625
873 Jordan 2019 4.452548 9.200901
874 Jordan 2020 4.093992 9.149995
875 Kazakhstan 2006 5.475948 9.804373
876 Kazakhstan 2007 5.718554 9.878194
877 Kazakhstan 2008 5.886420 9.898478
878 Kazakhstan 2009 5.382563 9.884036
879 Kazakhstan 2010 5.514287 9.940362
880 Kazakhstan 2011 5.735663 9.997437
881 Kazakhstan 2012 5.759470 10.030233
882 Kazakhstan 2013 5.835483 10.074108
883 Kazakhstan 2014 5.970098 10.100524
884 Kazakhstan 2015 5.949995 10.097837
885 Kazakhstan 2016 5.533552 10.094557
886 Kazakhstan 2017 5.882351 10.121135
887 Kazakhstan 2018 6.007636 10.148169
888 Kazakhstan 2019 6.272268 10.179278
889 Kazakhstan 2020 6.168269 10.135336
890 Kenya 2006 4.223234 8.038949
891 Kenya 2007 4.575658 8.077526
892 Kenya 2008 4.015275 8.052174
893 Kenya 2009 4.270435 8.057199
894 Kenya 2010 4.255859 8.110683
895 Kenya 2011 4.405310 8.143036
896 Kenya 2012 4.547335 8.161031
897 Kenya 2013 3.795383 8.191969
898 Kenya 2014 4.904580 8.218560
899 Kenya 2015 4.357618 8.249250
900 Kenya 2016 4.396128 8.282166
901 Kenya 2017 4.475654 8.305535
902 Kenya 2018 4.655703 8.343744
903 Kenya 2019 4.618850 8.373293
904 Kenya 2020 4.546584 8.365282
905 Kosovo 2007 5.103906 8.927753
906 Kosovo 2008 5.521660 8.980872
907 Kosovo 2009 5.891433 9.008162
908 Kosovo 2010 5.176601 9.032693
909 Kosovo 2011 4.859502 9.066925
910 Kosovo 2012 5.639588 9.085688
911 Kosovo 2013 6.125758 9.113430
912 Kosovo 2014 5.000375 9.128522
913 Kosovo 2015 5.077461 9.182307
914 Kosovo 2016 5.759412 9.228177
915 Kosovo 2017 6.149200 9.262030
916 Kosovo 2018 6.391826 9.296085
917 Kosovo 2019 6.425144 9.338535
918 Kosovo 2020 6.294414 NaN
919 Kuwait 2006 6.075547 11.228230
920 Kuwait 2009 6.585246 11.064857
921 Kuwait 2010 6.798151 10.982072
922 Kuwait 2011 6.377699 11.016783
923 Kuwait 2012 6.221095 11.025439
924 Kuwait 2013 6.480031 10.985214
925 Kuwait 2014 6.180139 10.944600
926 Kuwait 2015 6.146032 10.912070
927 Kuwait 2016 5.947195 10.909778
928 Kuwait 2017 6.093905 10.836743
929 Kuwait 2019 6.106120 10.816696
930 Kyrgyzstan 2006 4.641399 8.185375
931 Kyrgyzstan 2007 4.697762 8.257814
932 Kyrgyzstan 2008 4.736588 8.328985
933 Kyrgyzstan 2009 5.069054 8.345366
934 Kyrgyzstan 2010 4.996411 8.328712
935 Kyrgyzstan 2011 4.921049 8.374398
936 Kyrgyzstan 2012 5.207786 8.356864
937 Kyrgyzstan 2013 5.402427 8.440616
938 Kyrgyzstan 2014 5.252193 8.460006
939 Kyrgyzstan 2015 4.905376 8.477442
940 Kyrgyzstan 2016 4.856534 8.499515
941 Kyrgyzstan 2017 5.629537 8.526488
942 Kyrgyzstan 2018 5.297383 8.543475
943 Kyrgyzstan 2019 5.685221 8.566573
944 Kyrgyzstan 2020 6.249586 8.503411
945 Laos 2006 5.076226 8.250724
946 Laos 2007 5.363855 8.307173
947 Laos 2008 5.044099 8.365554
948 Laos 2011 4.703750 8.548466
949 Laos 2012 4.876085 8.610508
950 Laos 2017 4.623141 8.889833
951 Laos 2018 4.859402 8.934958
952 Laos 2019 5.196856 8.965257
953 Laos 2020 5.284391 8.959955
954 Latvia 2006 4.709502 10.032048
955 Latvia 2007 4.666972 10.135619
956 Latvia 2008 5.145375 10.112092
957 Latvia 2009 4.668911 9.975006
958 Latvia 2011 4.966812 10.029216
959 Latvia 2012 5.125025 10.082130
960 Latvia 2013 5.069770 10.115854
961 Latvia 2014 5.729115 10.144242
962 Latvia 2015 5.880598 10.184513
963 Latvia 2016 5.940446 10.211235
964 Latvia 2017 5.977818 10.257271
965 Latvia 2018 5.901154 10.307017
966 Latvia 2019 5.969754 10.336246
967 Latvia 2020 6.229009 10.299590
968 Lebanon 2005 5.491245 9.565474
969 Lebanon 2006 4.653104 9.567953
970 Lebanon 2008 4.594851 9.742742
971 Lebanon 2009 5.205999 9.830077
972 Lebanon 2010 5.031899 9.878128
973 Lebanon 2011 5.187572 9.837661
974 Lebanon 2012 4.572567 9.800110
975 Lebanon 2013 4.983289 9.771832
976 Lebanon 2014 5.233026 9.739010
977 Lebanon 2015 5.171971 9.698873
978 Lebanon 2016 5.270724 9.687102
979 Lebanon 2017 5.153990 9.680673
980 Lebanon 2018 5.167187 9.655796
981 Lebanon 2019 4.024220 9.596783
982 Lesotho 2011 4.897515 7.777329
983 Lesotho 2016 3.808205 7.952509
984 Lesotho 2017 3.795301 7.931326
985 Lesotho 2019 3.511781 7.925777
986 Liberia 2007 3.701401 7.195504
987 Liberia 2008 4.221354 7.223229
988 Liberia 2010 4.196063 7.258445
989 Liberia 2014 4.571419 7.391012
990 Liberia 2015 2.701591 7.365483
991 Liberia 2016 3.354676 7.324065
992 Liberia 2017 4.424491 7.323595
993 Liberia 2018 4.134853 7.311222
994 Liberia 2019 5.121461 7.263904
995 Libya 2012 5.754394 9.841973
996 Libya 2015 5.615405 9.307688
997 Libya 2016 5.433583 9.267895
998 Libya 2017 5.646852 9.490847
999 Libya 2018 5.493978 9.617004
1000 Libya 2019 5.330222 9.627350
1001 Lithuania 2006 5.954443 10.045794
1002 Lithuania 2007 5.808285 10.162817
1003 Lithuania 2008 5.553926 10.199043
1004 Lithuania 2009 5.466921 10.049811
1005 Lithuania 2010 5.065825 10.085495
1006 Lithuania 2011 5.432437 10.166590
1007 Lithuania 2012 5.771037 10.217619
1008 Lithuania 2013 5.595689 10.262704
1009 Lithuania 2014 6.125724 10.305781
1010 Lithuania 2015 5.711378 10.335316
1011 Lithuania 2016 5.865552 10.373261
1012 Lithuania 2017 6.272941 10.428843
1013 Lithuania 2018 6.308879 10.474184
1014 Lithuania 2019 6.064098 10.517996
1015 Lithuania 2020 6.391379 10.503607
1016 Luxembourg 2009 6.957920 11.562458
1017 Luxembourg 2010 7.097252 11.591707
1018 Luxembourg 2011 7.101400 11.594556
1019 Luxembourg 2012 6.964097 11.567009
1020 Luxembourg 2013 7.130809 11.579789
1021 Luxembourg 2014 6.891127 11.598289
1022 Luxembourg 2015 6.701571 11.616853
1023 Luxembourg 2016 6.967341 11.640030
1024 Luxembourg 2017 7.061381 11.633572
1025 Luxembourg 2018 7.242631 11.644917
1026 Luxembourg 2019 7.404016 11.648169
1027 Madagascar 2006 3.979751 7.375728
1028 Madagascar 2008 4.640079 7.438793
1029 Madagascar 2011 4.381415 7.336246
1030 Madagascar 2012 3.550610 7.338574
1031 Madagascar 2013 3.815607 7.334185
1032 Madagascar 2014 3.675627 7.340022
1033 Madagascar 2015 3.592514 7.343922
1034 Madagascar 2016 3.663086 7.356195
1035 Madagascar 2017 4.078620 7.367975
1036 Madagascar 2018 4.070587 7.385916
1037 Madagascar 2019 4.339087 7.406237
1038 Malawi 2006 3.829868 6.678227
1039 Malawi 2007 4.891037 6.741916
1040 Malawi 2009 5.148240 6.838264
1041 Malawi 2011 3.946063 6.894792
1042 Malawi 2012 4.279270 6.884888
1043 Malawi 2013 4.035084 6.907197
1044 Malawi 2014 4.563080 6.934600
1045 Malawi 2015 3.867638 6.934621
1046 Malawi 2016 3.476493 6.932059
1047 Malawi 2017 3.416863 6.944613
1048 Malawi 2018 3.334634 6.949402
1049 Malawi 2019 3.869124 6.965763
1050 Malaysia 2006 6.011717 9.839272
1051 Malaysia 2007 6.238904 9.880765
1052 Malaysia 2008 5.806782 9.908837
1053 Malaysia 2009 5.384702 9.875430
1054 Malaysia 2010 5.580282 9.930140
1055 Malaysia 2011 5.786367 9.966146
1056 Malaysia 2012 5.914284 10.004979
1057 Malaysia 2013 5.770200 10.037157
1058 Malaysia 2014 5.962922 10.082084
1059 Malaysia 2015 6.322121 10.118296
1060 Malaysia 2018 5.338818 10.223283
1061 Malaysia 2019 5.427954 10.252403
1062 Maldives 2018 5.197575 9.825986
1063 Mali 2006 4.014076 7.592930
1064 Mali 2008 4.114664 7.607233
1065 Mali 2009 3.976599 7.621565
1066 Mali 2010 3.762305 7.641754
1067 Mali 2011 4.666833 7.642934
1068 Mali 2012 4.313017 7.605007
1069 Mali 2013 3.676277 7.598773
1070 Mali 2014 3.974714 7.638360
1071 Mali 2015 4.582098 7.668848
1072 Mali 2016 4.016028 7.695135
1073 Mali 2017 4.741850 7.717912
1074 Mali 2018 4.415730 7.733290
1075 Mali 2019 4.987992 7.752495
1076 Malta 2009 6.327640 10.331231
1077 Malta 2010 5.773875 10.361134
1078 Malta 2011 6.154718 10.370396
1079 Malta 2012 5.962872 10.388962
1080 Malta 2013 6.379925 10.422175
1081 Malta 2014 6.452118 10.486463
1082 Malta 2015 6.613394 10.565676
1083 Malta 2016 6.590842 10.599454
1084 Malta 2017 6.675666 10.634771
1085 Malta 2018 6.909711 10.670444
1086 Malta 2019 6.732977 10.676836
1087 Malta 2020 6.156823 NaN
1088 Mauritania 2007 4.149043 8.533192
1089 Mauritania 2008 4.248075 8.501031
1090 Mauritania 2009 4.500432 8.472956
1091 Mauritania 2010 4.772307 8.469553
1092 Mauritania 2011 4.784804 8.480979
1093 Mauritania 2012 4.673204 8.495164
1094 Mauritania 2013 4.199015 8.506342
1095 Mauritania 2014 4.482805 8.518929
1096 Mauritania 2015 3.922664 8.542361
1097 Mauritania 2016 4.472149 8.526330
1098 Mauritania 2017 4.678160 8.532515
1099 Mauritania 2018 4.313615 8.525642
1100 Mauritania 2019 4.152619 8.555842
1101 Mauritius 2011 5.477073 9.767368
1102 Mauritius 2014 5.647780 9.864758
1103 Mauritius 2016 5.610003 9.935322
1104 Mauritius 2017 6.174118 9.971852
1105 Mauritius 2018 5.881741 10.008217
1106 Mauritius 2019 6.241165 10.042786
1107 Mauritius 2020 6.015300 9.972017
1108 Mexico 2005 6.580658 9.787807
1109 Mexico 2007 6.525378 9.825010
1110 Mexico 2008 6.829036 9.821427
1111 Mexico 2009 6.962819 9.752354
1112 Mexico 2010 6.802389 9.787887
1113 Mexico 2011 6.909515 9.809915
1114 Mexico 2012 7.320185 9.832137
1115 Mexico 2013 7.442546 9.832432
1116 Mexico 2014 6.679831 9.847312
1117 Mexico 2015 6.236287 9.867251
1118 Mexico 2016 6.824173 9.883908
1119 Mexico 2017 6.410299 9.893229
1120 Mexico 2018 6.549579 9.903099
1121 Mexico 2019 6.431945 9.890728
1122 Mexico 2020 5.964221 9.782189
1123 Moldova 2006 5.102071 8.935841
1124 Moldova 2007 4.774918 8.967717
1125 Moldova 2008 5.502756 9.044728
1126 Moldova 2009 5.554374 8.984115
1127 Moldova 2010 5.589736 9.053706
1128 Moldova 2011 5.792263 9.110837
1129 Moldova 2012 5.995713 9.105053
1130 Moldova 2013 5.756059 9.191901
1131 Moldova 2014 5.917058 9.241297
1132 Moldova 2015 6.017472 9.245788
1133 Moldova 2016 5.577784 9.300414
1134 Moldova 2017 5.325531 9.363174
1135 Moldova 2018 5.682277 9.423275
1136 Moldova 2019 5.803451 9.475307
1137 Moldova 2020 5.811629 9.462110
1138 Mongolia 2007 4.609059 8.833219
1139 Mongolia 2008 4.493010 8.903909
1140 Mongolia 2010 4.585524 8.919961
1141 Mongolia 2011 5.031174 9.061063
1142 Mongolia 2012 4.885150 9.157819
1143 Mongolia 2013 4.912928 9.247997
1144 Mongolia 2014 4.824835 9.303862
1145 Mongolia 2015 4.982720 9.307735
1146 Mongolia 2016 5.057000 9.300219
1147 Mongolia 2017 5.333850 9.333601
1148 Mongolia 2018 5.464623 9.385602
1149 Mongolia 2019 5.562905 9.418149
1150 Mongolia 2020 6.011365 9.395559
1151 Montenegro 2007 5.196315 9.692938
1152 Montenegro 2009 4.801060 9.699058
1153 Montenegro 2010 5.455030 9.724202
1154 Montenegro 2011 5.223117 9.754926
1155 Montenegro 2012 5.218724 9.726468
1156 Montenegro 2013 5.074342 9.760366
1157 Montenegro 2014 5.282721 9.777077
1158 Montenegro 2015 5.124921 9.809857
1159 Montenegro 2016 5.304066 9.838692
1160 Montenegro 2017 5.614799 9.884665
1161 Montenegro 2018 5.650190 9.934432
1162 Montenegro 2019 5.386025 9.970144
1163 Montenegro 2020 5.722163 9.912668
1164 Morocco 2010 4.383247 8.745781
1165 Morocco 2011 5.084973 8.783417
1166 Morocco 2012 4.969656 8.799099
1167 Morocco 2013 5.142160 8.829243
1168 Morocco 2015 5.163157 8.872023
1169 Morocco 2016 5.386307 8.869151
1170 Morocco 2017 5.312483 8.897567
1171 Morocco 2018 4.896792 8.914309
1172 Morocco 2019 5.056752 8.924619
1173 Morocco 2020 4.802618 8.870917
1174 Mozambique 2006 4.594880 6.775823
1175 Mozambique 2007 4.832635 6.822544
1176 Mozambique 2008 4.653583 6.865446
1177 Mozambique 2011 4.971112 6.978660
1178 Mozambique 2015 4.549767 7.140939
1179 Mozambique 2017 4.279863 7.157471
1180 Mozambique 2018 4.653714 7.162043
1181 Mozambique 2019 4.932133 7.154967
1182 Myanmar 2012 4.438940 8.157996
1183 Myanmar 2013 4.175671 8.230396
1184 Myanmar 2014 4.786247 8.299047
1185 Myanmar 2015 4.223846 8.359018
1186 Myanmar 2016 4.623120 8.408031
1187 Myanmar 2017 4.154342 8.463774
1188 Myanmar 2018 4.410633 8.523012
1189 Myanmar 2019 4.434237 8.545227
1190 Myanmar 2020 4.431364 8.553914
1191 Namibia 2007 4.885587 9.059242
1192 Namibia 2014 4.573991 9.231745
1193 Namibia 2017 4.441306 9.215378
1194 Namibia 2018 4.834088 9.203514
1195 Namibia 2019 4.435811 9.173384
1196 Namibia 2020 4.451010 9.104139
1197 Nepal 2006 4.566595 7.616336
1198 Nepal 2007 4.748284 7.637837
1199 Nepal 2008 4.440526 7.686386
1200 Nepal 2009 4.916868 7.722617
1201 Nepal 2010 4.349675 7.764844
1202 Nepal 2011 3.809445 7.797446
1203 Nepal 2012 4.233245 7.846059
1204 Nepal 2013 4.604577 7.889188
1205 Nepal 2014 4.975015 7.947761
1206 Nepal 2015 4.812437 7.976440
1207 Nepal 2016 5.099540 7.973241
1208 Nepal 2017 4.736692 8.038934
1209 Nepal 2018 4.910087 8.087254
1210 Nepal 2019 5.448725 8.136457
1211 Netherlands 2005 7.463979 10.813766
1212 Netherlands 2007 7.451880 10.881042
1213 Netherlands 2008 7.631012 10.898621
1214 Netherlands 2010 7.501876 10.864328
1215 Netherlands 2011 7.563798 10.875057
1216 Netherlands 2012 7.470716 10.861000
1217 Netherlands 2013 7.406550 10.856749
1218 Netherlands 2014 7.321188 10.867284
1219 Netherlands 2015 7.324437 10.882255
1220 Netherlands 2016 7.540877 10.898613
1221 Netherlands 2017 7.458965 10.921394
1222 Netherlands 2018 7.463097 10.941197
1223 Netherlands 2019 7.425269 10.953283
1224 Netherlands 2020 7.504448 10.900500
1225 New Zealand 2006 7.305014 10.525517
1226 New Zealand 2007 7.604173 10.546432
1227 New Zealand 2008 7.381171 10.527592
1228 New Zealand 2010 7.223756 10.520456
1229 New Zealand 2011 7.190638 10.536145
1230 New Zealand 2012 7.249630 10.552812
1231 New Zealand 2013 7.280152 10.571076
1232 New Zealand 2014 7.305892 10.591587
1233 New Zealand 2015 7.418121 10.608247
1234 New Zealand 2016 7.225688 10.623369
1235 New Zealand 2017 7.327183 10.633281
1236 New Zealand 2018 7.370286 10.660436
1237 New Zealand 2019 7.205174 10.666336
1238 New Zealand 2020 7.257382 10.600457
1239 Nicaragua 2006 4.460158 8.398162
1240 Nicaragua 2007 4.944091 8.433932
1241 Nicaragua 2008 5.103827 8.453972
1242 Nicaragua 2009 5.352805 8.406804
1243 Nicaragua 2010 5.686699 8.436372
1244 Nicaragua 2011 5.385705 8.484162
1245 Nicaragua 2012 5.448006 8.533731
1246 Nicaragua 2013 5.772275 8.568552
1247 Nicaragua 2014 6.275267 8.602145
1248 Nicaragua 2015 5.924113 8.635926
1249 Nicaragua 2016 6.012740 8.667662
1250 Nicaragua 2017 6.476357 8.700187
1251 Nicaragua 2018 5.818953 8.647322
1252 Nicaragua 2019 6.112545 8.595469
1253 Niger 2006 3.736952 6.887672
1254 Niger 2007 4.277402 6.880663
1255 Niger 2008 4.235657 6.917747
1256 Niger 2009 4.267170 6.898063
1257 Niger 2010 4.101016 6.940521
1258 Niger 2011 4.555830 6.925129
1259 Niger 2012 3.798088 6.986891
1260 Niger 2013 3.716330 7.001983
1261 Niger 2014 4.180943 7.026563
1262 Niger 2015 3.671454 7.030498
1263 Niger 2016 4.234646 7.047224
1264 Niger 2017 4.615674 7.057603
1265 Niger 2018 5.164007 7.087135
1266 Niger 2019 5.003544 7.105849
1267 Nigeria 2006 4.709746 8.326130
1268 Nigeria 2007 4.890419 8.363639
1269 Nigeria 2008 4.938560 8.402596
1270 Nigeria 2009 4.980220 8.453269
1271 Nigeria 2010 4.760276 8.503568
1272 Nigeria 2012 5.492954 8.543129
1273 Nigeria 2013 4.817869 8.580942
1274 Nigeria 2015 4.932915 8.615186
1275 Nigeria 2016 5.219568 8.572607
1276 Nigeria 2017 5.321928 8.554557
1277 Nigeria 2018 5.252288 8.547737
1278 Nigeria 2019 4.356419 8.543932
1279 Nigeria 2020 5.502948 8.484203
1280 North Cyprus 2012 5.463305 NaN
1281 North Cyprus 2013 5.566803 NaN
1282 North Cyprus 2014 5.785979 NaN
1283 North Cyprus 2015 5.842550 NaN
1284 North Cyprus 2016 5.827128 NaN
1285 North Cyprus 2018 5.608056 NaN
1286 North Cyprus 2019 5.466615 NaN
1287 North Macedonia 2007 4.493598 9.416016
1288 North Macedonia 2009 4.428022 9.463950
1289 North Macedonia 2010 4.180202 9.496163
1290 North Macedonia 2011 4.898180 9.518450
1291 North Macedonia 2012 4.639647 9.513014
1292 North Macedonia 2013 5.186191 9.540985
1293 North Macedonia 2014 5.203826 9.575810
1294 North Macedonia 2015 4.975590 9.612898
1295 North Macedonia 2016 5.345746 9.640300
1296 North Macedonia 2017 5.233867 9.650458
1297 North Macedonia 2018 5.239835 9.676835
1298 North Macedonia 2019 5.015485 9.711485
1299 North Macedonia 2020 5.053664 9.690015
1300 Norway 2006 7.415682 11.030973
1301 Norway 2008 7.632288 11.042418
1302 Norway 2012 7.678277 11.017255
1303 Norway 2014 7.444471 11.023678
1304 Norway 2015 7.603434 11.033208
1305 Norway 2016 7.596332 11.035056
1306 Norway 2017 7.578745 11.049947
1307 Norway 2018 7.444262 11.056159
1308 Norway 2019 7.442140 11.060889
1309 Norway 2020 7.290032 11.042160
1310 Oman 2011 6.852982 10.382462
1311 Pakistan 2005 5.224658 8.217931
1312 Pakistan 2007 5.671461 8.276694
1313 Pakistan 2008 4.413919 8.270934
1314 Pakistan 2009 5.208147 8.276524
1315 Pakistan 2010 5.786133 8.270493
1316 Pakistan 2011 5.267186 8.276015
1317 Pakistan 2012 5.131565 8.289218
1318 Pakistan 2013 5.138083 8.311207
1319 Pakistan 2014 5.435658 8.335972
1320 Pakistan 2015 4.823195 8.361321
1321 Pakistan 2016 5.548508 8.394273
1322 Pakistan 2017 5.830871 8.427578
1323 Pakistan 2018 5.471554 8.463744
1324 Pakistan 2019 4.442718 8.453291
1325 Palestinian Territories 2006 4.716388 8.212757
1326 Palestinian Territories 2007 4.151054 8.218426
1327 Palestinian Territories 2008 4.385603 8.275765
1328 Palestinian Territories 2009 4.470191 8.328596
1329 Palestinian Territories 2010 4.702604 8.383216
1330 Palestinian Territories 2011 4.751220 8.474425
1331 Palestinian Territories 2012 4.646608 8.530910
1332 Palestinian Territories 2013 4.844028 8.488586
1333 Palestinian Territories 2014 4.721938 8.457089
1334 Palestinian Territories 2015 4.695239 8.480025
1335 Palestinian Territories 2016 4.906618 8.498220
1336 Palestinian Territories 2017 4.628133 8.484533
1337 Palestinian Territories 2018 4.553922 NaN
1338 Palestinian Territories 2019 4.482537 NaN
1339 Panama 2006 6.127988 9.763903
1340 Panama 2007 6.894140 9.858971
1341 Panama 2008 6.930903 9.935025
1342 Panama 2009 7.033740 9.929617
1343 Panama 2010 7.321467 9.968682
1344 Panama 2011 7.248081 10.058502
1345 Panama 2012 6.859836 10.134644
1346 Panama 2013 6.866480 10.184355
1347 Panama 2014 6.631171 10.216750
1348 Panama 2015 6.605550 10.255424
1349 Panama 2016 6.117638 10.286634
1350 Panama 2017 6.567659 10.323997
1351 Panama 2018 6.281434 10.343328
1352 Panama 2019 6.085955 10.356431
1353 Paraguay 2006 4.730082 9.087580
1354 Paraguay 2007 5.272461 9.126068
1355 Paraguay 2008 5.570062 9.173999
1356 Paraguay 2009 5.576147 9.157912
1357 Paraguay 2010 5.841174 9.250023
1358 Paraguay 2011 5.677081 9.277973
1359 Paraguay 2012 5.820058 9.258847
1360 Paraguay 2013 5.936241 9.325938
1361 Paraguay 2014 5.118642 9.359787
1362 Paraguay 2015 5.559724 9.376698
1363 Paraguay 2016 5.801380 9.405685
1364 Paraguay 2017 5.713295 9.441003
1365 Paraguay 2019 5.652626 9.448144
1366 Peru 2006 4.810845 8.989351
1367 Peru 2007 5.213962 9.062915
1368 Peru 2008 5.129231 9.142194
1369 Peru 2009 5.518847 9.145060
1370 Peru 2010 5.612785 9.216966
1371 Peru 2011 5.892457 9.270197
1372 Peru 2012 5.824557 9.321531
1373 Peru 2013 5.782557 9.369393
1374 Peru 2014 5.865816 9.382366
1375 Peru 2015 5.577263 9.401809
1376 Peru 2016 5.700629 9.425749
1377 Peru 2017 5.710937 9.434006
1378 Peru 2018 5.679661 9.455823
1379 Peru 2019 5.999382 9.460935
1380 Philippines 2006 4.669946 8.561845
1381 Philippines 2007 5.073562 8.607889
1382 Philippines 2008 4.589065 8.633818
1383 Philippines 2009 4.879911 8.631698
1384 Philippines 2010 4.941514 8.685817
1385 Philippines 2011 4.993957 8.706756
1386 Philippines 2012 5.001965 8.756410
1387 Philippines 2013 4.976925 8.804813
1388 Philippines 2014 5.312550 8.849893
1389 Philippines 2015 5.547489 8.895648
1390 Philippines 2016 5.430833 8.949631
1391 Philippines 2017 5.594270 9.002189
1392 Philippines 2018 5.869173 9.049713
1393 Philippines 2019 6.267745 9.094725
1394 Philippines 2020 5.079585 9.061443
1395 Poland 2005 5.587209 9.848785
1396 Poland 2007 5.886137 9.977909
1397 Poland 2009 5.772027 10.046525
1398 Poland 2010 5.887030 10.084822
1399 Poland 2011 5.646205 10.133238
1400 Poland 2012 5.875932 10.149192
1401 Poland 2013 5.746132 10.163618
1402 Poland 2014 5.750282 10.197012
1403 Poland 2015 6.007022 10.235351
1404 Poland 2016 6.162076 10.265960
1405 Poland 2017 6.201268 10.314032
1406 Poland 2018 6.111485 10.366142
1407 Poland 2019 6.242094 10.406878
1408 Poland 2020 6.139455 10.371203
1409 Portugal 2006 5.405246 10.359779
1410 Portugal 2008 5.716967 10.384319
1411 Portugal 2010 5.094526 10.368415
1412 Portugal 2011 5.219998 10.352778
1413 Portugal 2012 4.993962 10.315413
1414 Portugal 2013 5.157688 10.311633
1415 Portugal 2014 5.126912 10.324915
1416 Portugal 2015 5.080866 10.346819
1417 Portugal 2016 5.446637 10.369967
1418 Portugal 2017 5.711499 10.406869
1419 Portugal 2018 5.919823 10.434500
1420 Portugal 2019 6.095473 10.457315
1421 Portugal 2020 5.767792 10.370820
1422 Qatar 2009 6.417824 11.455724
1423 Qatar 2010 6.849653 11.519814
1424 Qatar 2011 6.591604 11.553021
1425 Qatar 2012 6.611299 11.523082
1426 Qatar 2015 6.374529 11.485615
1427 Romania 2005 5.048648 9.724312
1428 Romania 2007 5.393724 9.892077
1429 Romania 2009 5.367565 9.949312
1430 Romania 2010 4.909166 9.915458
1431 Romania 2011 5.022758 9.940249
1432 Romania 2012 5.166875 9.965261
1433 Romania 2013 5.081584 10.003515
1434 Romania 2014 5.726893 10.040800
1435 Romania 2015 5.777491 10.083486
1436 Romania 2016 5.968871 10.136113
1437 Romania 2017 6.089905 10.210666
1438 Romania 2018 6.150879 10.259953
1439 Romania 2019 6.129942 10.305914
1440 Russia 2006 4.963743 9.990775
1441 Russia 2007 5.222867 10.074066
1442 Russia 2008 5.618754 10.125198
1443 Russia 2009 5.158228 10.043687
1444 Russia 2010 5.384773 10.087255
1445 Russia 2011 5.388766 10.128576
1446 Russia 2012 5.620736 10.166346
1447 Russia 2013 5.537178 10.181619
1448 Russia 2014 6.036977 10.171111
1449 Russia 2015 5.995539 10.149030
1450 Russia 2016 5.854946 10.149133
1451 Russia 2017 5.578743 10.166081
1452 Russia 2018 5.513500 10.191209
1453 Russia 2019 5.440524 10.205218
1454 Russia 2020 5.495289 10.162235
1455 Rwanda 2006 4.214704 7.111424
1456 Rwanda 2008 4.362989 7.238954
1457 Rwanda 2009 4.029762 7.272810
1458 Rwanda 2011 4.097436 7.369293
1459 Rwanda 2012 3.333048 7.427577
1460 Rwanda 2013 3.466388 7.449177
1461 Rwanda 2014 3.595678 7.484139
1462 Rwanda 2015 3.483109 7.543681
1463 Rwanda 2016 3.332990 7.575755
1464 Rwanda 2017 3.108374 7.588451
1465 Rwanda 2018 3.561047 7.644233
1466 Rwanda 2019 3.268152 7.708061
1467 Saudi Arabia 2005 7.079644 10.698955
1468 Saudi Arabia 2007 7.266694 10.688892
1469 Saudi Arabia 2008 6.811370 10.721947
1470 Saudi Arabia 2009 6.147590 10.672890
1471 Saudi Arabia 2010 6.307098 10.692780
1472 Saudi Arabia 2011 6.699790 10.757668
1473 Saudi Arabia 2012 6.396359 10.779456
1474 Saudi Arabia 2013 6.495133 10.775777
1475 Saudi Arabia 2014 6.278378 10.783291
1476 Saudi Arabia 2015 6.345492 10.797967
1477 Saudi Arabia 2016 6.473921 10.791937
1478 Saudi Arabia 2017 6.294282 10.764459
1479 Saudi Arabia 2018 6.356393 10.770519
1480 Saudi Arabia 2019 6.561247 10.757097
1481 Saudi Arabia 2020 6.559588 10.700663
1482 Senegal 2006 4.417353 7.880945
1483 Senegal 2007 4.679987 7.902722
1484 Senegal 2008 4.683500 7.915670
1485 Senegal 2009 4.335114 7.909231
1486 Senegal 2010 4.372156 7.916806
1487 Senegal 2011 3.834202 7.903617
1488 Senegal 2012 3.668737 7.925668
1489 Senegal 2013 3.647367 7.925508
1490 Senegal 2014 4.394777 7.961481
1491 Senegal 2015 4.617001 7.995122
1492 Senegal 2016 4.594534 8.028671
1493 Senegal 2017 4.683025 8.072124
1494 Senegal 2018 4.769377 8.106148
1495 Senegal 2019 5.488737 8.130020
1496 Serbia 2007 4.750384 9.531929
1497 Serbia 2009 4.380312 9.567513
1498 Serbia 2010 4.461304 9.578816
1499 Serbia 2011 4.815187 9.606869
1500 Serbia 2012 5.154522 9.604883
1501 Serbia 2013 5.101840 9.638266
1502 Serbia 2014 5.112729 9.626937
1503 Serbia 2015 5.317685 9.649492
1504 Serbia 2016 5.752755 9.687587
1505 Serbia 2017 5.122031 9.713195
1506 Serbia 2018 5.936493 9.761643
1507 Serbia 2019 6.241407 9.808065
1508 Serbia 2020 6.041546 9.788260
1509 Sierra Leone 2006 3.628185 7.136178
1510 Sierra Leone 2007 3.585127 7.186534
1511 Sierra Leone 2008 2.997251 7.215358
1512 Sierra Leone 2010 4.133956 7.253870
1513 Sierra Leone 2011 4.501644 7.292360
1514 Sierra Leone 2013 4.514291 7.577167
1515 Sierra Leone 2014 4.499970 7.599658
1516 Sierra Leone 2015 4.908618 7.347185
1517 Sierra Leone 2016 4.732953 7.384333
1518 Sierra Leone 2017 4.089562 7.404040
1519 Sierra Leone 2018 4.305683 7.416554
1520 Sierra Leone 2019 3.447381 7.449132
1521 Singapore 2006 6.462703 11.167536
1522 Singapore 2007 6.833755 11.212256
1523 Singapore 2008 6.641957 11.177551
1524 Singapore 2009 6.144677 11.148601
1525 Singapore 2010 6.531402 11.266511
1526 Singapore 2011 6.561042 11.307114
1527 Singapore 2013 6.533207 11.357275
1528 Singapore 2014 7.062365 11.382915
1529 Singapore 2015 6.619525 11.400499
1530 Singapore 2016 6.033481 11.419444
1531 Singapore 2017 6.378438 11.461011
1532 Singapore 2018 6.374564 11.490117
1533 Singapore 2019 6.378360 11.485980
1534 Slovakia 2006 5.264677 10.015392
1535 Slovakia 2010 6.052223 10.168606
1536 Slovakia 2011 5.945048 10.195559
1537 Slovakia 2012 5.911059 10.212638
1538 Slovakia 2013 5.936527 10.218249
1539 Slovakia 2014 6.138873 10.244431
1540 Slovakia 2015 6.162004 10.290573
1541 Slovakia 2016 5.993163 10.310295
1542 Slovakia 2017 6.365509 10.338752
1543 Slovakia 2018 6.235111 10.375594
1544 Slovakia 2019 6.243429 10.397957
1545 Slovakia 2020 6.519098 10.331512
1546 Slovenia 2006 5.811265 10.402996
1547 Slovenia 2009 5.830161 10.410269
1548 Slovenia 2010 6.082555 10.419256
1549 Slovenia 2011 6.035964 10.425755
1550 Slovenia 2012 6.062891 10.396906
1551 Slovenia 2013 5.974889 10.385202
1552 Slovenia 2014 5.678395 10.411524
1553 Slovenia 2015 5.740642 10.432632
1554 Slovenia 2016 5.936821 10.462640
1555 Slovenia 2017 6.166838 10.509191
1556 Slovenia 2018 6.249419 10.545921
1557 Slovenia 2019 6.665274 10.563305
1558 Slovenia 2020 6.462076 10.477870
1559 Somalia 2014 5.528273 NaN
1560 Somalia 2015 5.353645 NaN
1561 Somalia 2016 4.667941 NaN
1562 Somaliland region 2009 4.991400 NaN
1563 Somaliland region 2010 4.657363 NaN
1564 Somaliland region 2011 4.930572 NaN
1565 Somaliland region 2012 5.057314 NaN
1566 South Africa 2006 5.083987 9.386314
1567 South Africa 2007 5.204454 9.425617
1568 South Africa 2008 5.346307 9.443687
1569 South Africa 2009 5.218431 9.414272
1570 South Africa 2010 4.652429 9.429664
1571 South Africa 2011 4.930511 9.446725
1572 South Africa 2012 5.133888 9.452785
1573 South Africa 2013 3.660727 9.461276
1574 South Africa 2014 4.828456 9.463746
1575 South Africa 2015 4.887326 9.460323
1576 South Africa 2016 4.769740 9.449658
1577 South Africa 2017 4.513655 9.449627
1578 South Africa 2018 4.883922 9.443890
1579 South Africa 2019 5.034863 9.432028
1580 South Africa 2020 4.946801 9.332463
1581 South Korea 2006 5.332178 10.309702
1582 South Korea 2007 5.767276 10.361026
1583 South Korea 2008 5.389625 10.383118
1584 South Korea 2009 5.647690 10.385866
1585 South Korea 2010 6.116024 10.446717
1586 South Korea 2011 6.946599 10.475221
1587 South Korea 2012 6.003287 10.493705
1588 South Korea 2013 5.958810 10.520309
1589 South Korea 2014 5.801325 10.545550
1590 South Korea 2015 5.780211 10.567981
1591 South Korea 2016 5.970564 10.593056
1592 South Korea 2017 5.873887 10.621353
1593 South Korea 2018 5.840231 10.642900
1594 South Korea 2019 5.902817 10.661044
1595 South Korea 2020 5.792696 10.648074
1596 South Sudan 2014 3.831992 NaN
1597 South Sudan 2015 4.070771 NaN
1598 South Sudan 2016 2.888112 NaN
1599 South Sudan 2017 2.816622 NaN
1600 Spain 2005 7.152786 10.546350
1601 Spain 2007 6.994615 10.586556
1602 Spain 2008 7.294473 10.579435
1603 Spain 2009 6.198601 10.532220
1604 Spain 2010 6.188262 10.529244
1605 Spain 2011 6.518249 10.517514
1606 Spain 2012 6.290690 10.486824
1607 Spain 2013 6.150027 10.475642
1608 Spain 2014 6.456478 10.492376
1609 Spain 2015 6.380663 10.530787
1610 Spain 2016 6.318612 10.559805
1611 Spain 2017 6.230173 10.585966
1612 Spain 2018 6.513371 10.604824
1613 Spain 2019 6.457449 10.618478
1614 Spain 2020 6.502175 10.488059
1615 Sri Lanka 2006 4.344611 8.911856
1616 Sri Lanka 2007 4.414805 8.970224
1617 Sri Lanka 2008 4.430846 9.020894
1618 Sri Lanka 2009 4.212027 9.048715
1619 Sri Lanka 2010 3.976905 9.118978
1620 Sri Lanka 2011 4.180569 9.192944
1621 Sri Lanka 2012 4.224593 9.279157
1622 Sri Lanka 2013 4.364694 9.304748
1623 Sri Lanka 2014 4.267933 9.343831
1624 Sri Lanka 2015 4.611607 9.383496
1625 Sri Lanka 2017 4.330945 9.440189
1626 Sri Lanka 2018 4.435024 9.462235
1627 Sri Lanka 2019 4.213299 9.478694
1628 Sudan 2009 4.454917 8.105703
1629 Sudan 2010 4.435160 8.076443
1630 Sudan 2011 4.314456 8.203635
1631 Sudan 2012 4.550499 8.295729
1632 Sudan 2014 4.138673 8.317068
1633 Suriname 2012 6.269287 9.797085
1634 Swaziland 2011 4.867091 8.940104
1635 Swaziland 2018 4.211565 9.060224
1636 Swaziland 2019 4.396115 9.069710
1637 Sweden 2005 7.376316 10.739267
1638 Sweden 2007 7.241363 10.805614
1639 Sweden 2008 7.515997 10.793308
1640 Sweden 2009 7.265977 10.740421
1641 Sweden 2010 7.496019 10.789714
1642 Sweden 2011 7.382232 10.813616
1643 Sweden 2012 7.560148 10.800318
1644 Sweden 2013 7.434011 10.803652
1645 Sweden 2014 7.239148 10.819961
1646 Sweden 2015 7.288922 10.853300
1647 Sweden 2016 7.368744 10.861230
1648 Sweden 2017 7.286805 10.873111
1649 Sweden 2018 7.374792 10.880807
1650 Sweden 2019 7.398093 10.881908
1651 Sweden 2020 7.314341 10.837904
1652 Switzerland 2006 7.473253 11.049914
1653 Switzerland 2009 7.524521 11.054919
1654 Switzerland 2012 7.776209 11.079147
1655 Switzerland 2014 7.492804 11.097996
1656 Switzerland 2015 7.572137 11.099858
1657 Switzerland 2016 7.458520 11.106019
1658 Switzerland 2017 7.473593 11.114521
1659 Switzerland 2018 7.508587 11.134289
1660 Switzerland 2019 7.694221 11.136454
1661 Switzerland 2020 7.508435 11.080893
1662 Syria 2008 5.323332 8.651800
1663 Syria 2009 4.978971 8.653676
1664 Syria 2010 4.464708 8.729084
1665 Syria 2011 4.037889 8.726923
1666 Syria 2012 3.164491 8.562601
1667 Syria 2013 2.687553 8.396470
1668 Syria 2015 3.461913 8.441537
1669 Taiwan Province of China 2006 6.189050 10.613232
1670 Taiwan Province of China 2008 5.547682 10.606202
1671 Taiwan Province of China 2010 6.228531 10.690681
1672 Taiwan Province of China 2011 6.308915 10.705154
1673 Taiwan Province of China 2012 6.125917 10.715845
1674 Taiwan Province of China 2013 6.340344 10.750063
1675 Taiwan Province of China 2014 6.363497 10.797789
1676 Taiwan Province of China 2015 6.450088 10.842318
1677 Taiwan Province of China 2016 6.512851 10.854927
1678 Taiwan Province of China 2017 6.359451 10.870996
1679 Taiwan Province of China 2018 6.467005 NaN
1680 Taiwan Province of China 2019 6.537090 NaN
1681 Taiwan Province of China 2020 6.751068 NaN
1682 Tajikistan 2006 4.613099 7.554471
1683 Tajikistan 2007 4.431609 7.609175
1684 Tajikistan 2008 5.063987 7.664672
1685 Tajikistan 2009 4.575175 7.681615
1686 Tajikistan 2010 4.380636 7.722940
1687 Tajikistan 2011 4.262671 7.771989
1688 Tajikistan 2012 4.496572 7.821405
1689 Tajikistan 2013 4.966521 7.869584
1690 Tajikistan 2014 4.896158 7.910819
1691 Tajikistan 2015 5.124211 7.945079
1692 Tajikistan 2016 5.103721 7.987065
1693 Tajikistan 2017 5.829234 8.035774
1694 Tajikistan 2018 5.497469 8.081698
1695 Tajikistan 2019 5.464015 8.125557
1696 Tajikistan 2020 5.373399 8.080357
1697 Tanzania 2006 3.922484 7.485086
1698 Tanzania 2007 4.317950 7.522392
1699 Tanzania 2008 4.384742 7.549336
1700 Tanzania 2009 3.407508 7.572010
1701 Tanzania 2010 3.229129 7.604382
1702 Tanzania 2011 4.073562 7.648876
1703 Tanzania 2012 4.006897 7.663198
1704 Tanzania 2013 3.852395 7.698932
1705 Tanzania 2014 3.483279 7.734119
1706 Tanzania 2015 3.660597 7.763930
1707 Tanzania 2016 2.902734 7.800395
1708 Tanzania 2017 3.347121 7.836148
1709 Tanzania 2018 3.445023 7.859404
1710 Tanzania 2019 3.640155 7.886240
1711 Tanzania 2020 3.785684 7.881270
1712 Thailand 2006 5.885433 9.461148
1713 Thailand 2007 5.783891 9.508475
1714 Thailand 2008 5.636471 9.520327
1715 Thailand 2009 5.475645 9.508361
1716 Thailand 2010 6.216703 9.575911
1717 Thailand 2011 6.663609 9.579475
1718 Thailand 2012 6.300235 9.644709
1719 Thailand 2013 6.231025 9.666691
1720 Thailand 2014 6.985464 9.672178
1721 Thailand 2015 6.201763 9.699015
1722 Thailand 2016 6.073640 9.729001
1723 Thailand 2017 5.938895 9.765407
1724 Thailand 2018 6.011562 9.802921
1725 Thailand 2019 6.022151 9.823529
1726 Thailand 2020 5.884544 9.769243
1727 Togo 2006 3.202429 7.077817
1728 Togo 2008 2.807855 7.051686
1729 Togo 2011 2.936221 7.145922
1730 Togo 2014 2.838959 7.247175
1731 Togo 2015 3.768302 7.277406
1732 Togo 2016 3.878578 7.306319
1733 Togo 2017 4.360805 7.324177
1734 Togo 2018 4.022895 7.347652
1735 Togo 2019 4.179494 7.375211
1736 Trinidad and Tobago 2006 5.832189 10.223845
1737 Trinidad and Tobago 2008 6.696444 10.294565
1738 Trinidad and Tobago 2011 6.518746 10.262998
1739 Trinidad and Tobago 2013 6.167707 10.284636
1740 Trinidad and Tobago 2017 6.191860 10.182920
1741 Tunisia 2009 5.025470 9.197462
1742 Tunisia 2010 5.130521 9.221612
1743 Tunisia 2011 4.876482 9.192277
1744 Tunisia 2012 4.463531 9.221737
1745 Tunisia 2013 5.245605 9.240366
1746 Tunisia 2014 4.763595 9.259631
1747 Tunisia 2015 5.131612 9.261008
1748 Tunisia 2016 4.521453 9.261508
1749 Tunisia 2017 4.124343 9.269105
1750 Tunisia 2018 4.741132 9.283942
1751 Tunisia 2019 4.315480 9.283180
1752 Tunisia 2020 4.730811 9.230624
1753 Turkey 2005 4.718734 9.809252
1754 Turkey 2007 5.623472 9.902598
1755 Turkey 2008 5.118232 9.899062
1756 Turkey 2009 5.212842 9.838136
1757 Turkey 2010 5.490347 9.905599
1758 Turkey 2011 5.271944 9.995656
1759 Turkey 2012 5.309076 10.026114
1760 Turkey 2013 4.888177 10.090672
1761 Turkey 2014 5.579794 10.124029
1762 Turkey 2015 5.514465 10.166448
1763 Turkey 2016 5.326222 10.181467
1764 Turkey 2017 5.607262 10.237606
1765 Turkey 2018 5.185689 10.250577
1766 Turkey 2019 4.872074 10.245920
1767 Turkey 2020 4.861554 10.219084
1768 Turkmenistan 2009 6.567713 8.989171
1769 Turkmenistan 2011 5.791755 9.181697
1770 Turkmenistan 2012 5.463827 9.268988
1771 Turkmenistan 2013 5.391763 9.347593
1772 Turkmenistan 2014 5.787379 9.427173
1773 Turkmenistan 2015 5.791460 9.472206
1774 Turkmenistan 2016 5.887052 9.515066
1775 Turkmenistan 2017 5.229149 9.561351
1776 Turkmenistan 2018 4.620602 9.605440
1777 Turkmenistan 2019 5.474300 9.651184
1778 Uganda 2006 3.733584 7.369865
1779 Uganda 2007 4.455839 7.419120
1780 Uganda 2008 4.568619 7.471063
1781 Uganda 2009 4.611986 7.505189
1782 Uganda 2010 4.192882 7.528168
1783 Uganda 2011 4.826001 7.586103
1784 Uganda 2012 4.309238 7.591943
1785 Uganda 2013 3.709579 7.594839
1786 Uganda 2014 3.769919 7.611118
1787 Uganda 2015 4.237687 7.626735
1788 Uganda 2016 4.233261 7.636911
1789 Uganda 2017 4.000517 7.637649
1790 Uganda 2018 4.321715 7.660166
1791 Uganda 2019 4.948051 7.687653
1792 Uganda 2020 4.640910 7.684450
1793 Ukraine 2006 4.803954 9.380307
1794 Ukraine 2007 5.252182 9.459466
1795 Ukraine 2008 5.172380 9.487659
1796 Ukraine 2009 5.165639 9.332416
1797 Ukraine 2010 5.057561 9.374015
1798 Ukraine 2011 5.083133 9.430825
1799 Ukraine 2012 5.030342 9.435678
1800 Ukraine 2013 4.710803 9.437689
1801 Ukraine 2014 4.297330 9.426173
1802 Ukraine 2015 3.964543 9.326974
1803 Ukraine 2016 4.028690 9.353109
1804 Ukraine 2017 4.311067 9.381865
1805 Ukraine 2018 4.661909 9.420440
1806 Ukraine 2019 4.701762 9.458004
1807 Ukraine 2020 5.269676 9.427874
1808 United Arab Emirates 2006 6.734222 11.367043
1809 United Arab Emirates 2009 6.866063 10.974636
1810 United Arab Emirates 2010 7.097456 10.913667
1811 United Arab Emirates 2011 7.118701 10.935309
1812 United Arab Emirates 2012 7.217767 10.957638
1813 United Arab Emirates 2013 6.620951 11.000794
1814 United Arab Emirates 2014 6.539855 11.040978
1815 United Arab Emirates 2015 6.568398 11.085503
1816 United Arab Emirates 2016 6.830950 11.105121
1817 United Arab Emirates 2017 7.039420 11.115185
1818 United Arab Emirates 2018 6.603744 11.111975
1819 United Arab Emirates 2019 6.710783 11.114224
1820 United Arab Emirates 2020 6.458392 11.052890
1821 United Kingdom 2005 6.983557 10.662885
1822 United Kingdom 2007 6.801931 10.699264
1823 United Kingdom 2008 6.986464 10.688578
1824 United Kingdom 2009 6.906547 10.637608
1825 United Kingdom 2010 7.029364 10.649076
1826 United Kingdom 2011 6.869249 10.656545
1827 United Kingdom 2012 6.880784 10.664272
1828 United Kingdom 2013 6.918055 10.678744
1829 United Kingdom 2014 6.758148 10.697121
1830 United Kingdom 2015 6.515445 10.712479
1831 United Kingdom 2016 6.824284 10.723900
1832 United Kingdom 2017 7.103273 10.735850
1833 United Kingdom 2018 7.233445 10.743109
1834 United Kingdom 2019 7.157151 10.751485
1835 United Kingdom 2020 6.798177 10.625811
1836 United States 2006 7.181794 10.923974
1837 United States 2007 7.512688 10.933051
1838 United States 2008 7.280386 10.922226
1839 United States 2009 7.158032 10.887765
1840 United States 2010 7.163616 10.904800
1841 United States 2011 7.115139 10.912990
1842 United States 2012 7.026227 10.927963
1843 United States 2013 7.249285 10.939349
1844 United States 2014 7.151114 10.956298
1845 United States 2015 6.863947 10.977393
1846 United States 2016 6.803600 10.985777
1847 United States 2017 6.991759 11.001395
1848 United States 2018 6.882685 11.025024
1849 United States 2019 6.943701 11.043353
1850 United States 2020 7.028088 11.000656
1851 Uruguay 2006 5.785868 9.542817
1852 Uruguay 2007 5.693946 9.604274
1853 Uruguay 2008 5.663870 9.671038
1854 Uruguay 2009 6.296223 9.709771
1855 Uruguay 2010 6.062011 9.782048
1856 Uruguay 2011 6.554047 9.829510
1857 Uruguay 2012 6.449728 9.861304
1858 Uruguay 2013 6.444465 9.903544
1859 Uruguay 2014 6.561444 9.932180
1860 Uruguay 2015 6.628080 9.932483
1861 Uruguay 2016 6.171485 9.945693
1862 Uruguay 2017 6.336010 9.967628
1863 Uruguay 2018 6.371715 9.980024
1864 Uruguay 2019 6.600337 9.978644
1865 Uruguay 2020 6.309681 9.937192
1866 Uzbekistan 2006 5.232322 8.192730
1867 Uzbekistan 2008 5.311368 8.339396
1868 Uzbekistan 2009 5.260721 8.399955
1869 Uzbekistan 2010 5.095342 8.444950
1870 Uzbekistan 2011 5.738744 8.493077
1871 Uzbekistan 2012 6.019332 8.549520
1872 Uzbekistan 2013 5.939986 8.607008
1873 Uzbekistan 2014 6.049212 8.659472
1874 Uzbekistan 2015 5.972364 8.713864
1875 Uzbekistan 2016 5.892539 8.755632
1876 Uzbekistan 2017 6.421448 8.782446
1877 Uzbekistan 2018 6.205460 8.818110
1878 Uzbekistan 2019 6.154049 8.853480
1879 Venezuela 2005 7.169621 9.313096
1880 Venezuela 2006 6.525146 9.459522
1881 Venezuela 2008 6.257771 9.700688
1882 Venezuela 2009 7.188803 9.542343
1883 Venezuela 2010 7.478455 9.716555
1884 Venezuela 2011 6.579789 9.822392
1885 Venezuela 2012 7.066577 9.826082
1886 Venezuela 2013 6.552796 9.738845
1887 Venezuela 2014 6.136096 9.557058
1888 Venezuela 2015 5.568800 9.001046
1889 Venezuela 2016 4.041115 9.010295
1890 Venezuela 2017 5.070751 9.073104
1891 Venezuela 2018 5.005663 NaN
1892 Venezuela 2019 5.080803 NaN
1893 Venezuela 2020 4.573830 NaN
1894 Vietnam 2006 5.293660 8.334977
1895 Vietnam 2007 5.421688 8.394412
1896 Vietnam 2008 5.480425 8.439887
1897 Vietnam 2009 5.304265 8.482665
1898 Vietnam 2010 5.295781 8.534918
1899 Vietnam 2011 5.767344 8.585228
1900 Vietnam 2012 5.534570 8.625951
1901 Vietnam 2013 5.022699 8.668217
1902 Vietnam 2014 5.084923 8.715796
1903 Vietnam 2015 5.076315 8.770014
1904 Vietnam 2016 5.062267 8.819946
1905 Vietnam 2017 5.175279 8.875670
1906 Vietnam 2018 5.295547 8.934111
1907 Vietnam 2019 5.467451 8.992331
1908 Yemen 2007 4.477133 8.214067
1909 Yemen 2009 4.809259 8.277721
1910 Yemen 2010 4.350313 8.453350
1911 Yemen 2011 3.746256 8.336312
1912 Yemen 2012 4.060601 8.236007
1913 Yemen 2013 4.217679 8.241937
1914 Yemen 2014 3.967958 8.116539
1915 Yemen 2015 2.982674 7.857512
1916 Yemen 2016 3.825631 7.715108
1917 Yemen 2017 3.253560 7.578437
1918 Yemen 2018 3.057514 NaN
1919 Yemen 2019 4.196913 NaN
1920 Zambia 2006 4.824455 7.817309
1921 Zambia 2007 3.998293 7.870825
1922 Zambia 2008 4.730263 7.918427
1923 Zambia 2009 5.260361 7.978490
1924 Zambia 2011 4.999114 8.071311
1925 Zambia 2012 5.013375 8.113511
1926 Zambia 2013 5.243996 8.131451
1927 Zambia 2014 4.345837 8.146145
1928 Zambia 2015 4.843164 8.144258
1929 Zambia 2016 4.347544 8.151297
1930 Zambia 2017 3.932777 8.156224
1931 Zambia 2018 4.041488 8.166652
1932 Zambia 2019 3.306797 8.154642
1933 Zambia 2020 4.837992 8.116580
1934 Zimbabwe 2006 3.826268 7.711109
1935 Zimbabwe 2007 3.280247 7.665664
1936 Zimbabwe 2008 3.174264 7.461205
1937 Zimbabwe 2009 4.055914 7.562871
1938 Zimbabwe 2010 4.681570 7.728944
1939 Zimbabwe 2011 4.845642 7.846308
1940 Zimbabwe 2012 4.955101 7.983468
1941 Zimbabwe 2013 4.690188 7.985391
1942 Zimbabwe 2014 4.184451 7.991335
1943 Zimbabwe 2015 3.703191 7.992339
1944 Zimbabwe 2016 3.735400 7.984372
1945 Zimbabwe 2017 3.638300 8.015738
1946 Zimbabwe 2018 3.616480 8.048798
1947 Zimbabwe 2019 2.693523 7.950132
1948 Zimbabwe 2020 3.159802 7.828757
Social support Healthy life expectancy at birth \
0 0.450662 50.799999
1 0.552308 51.200001
2 0.539075 51.599998
3 0.521104 51.919998
4 0.520637 52.240002
5 0.483552 52.560001
6 0.525568 52.880001
7 0.528597 53.200001
8 0.559072 53.000000
9 0.490880 52.799999
10 0.507516 52.599998
11 0.419973 52.400002
12 0.821372 65.800003
13 0.833047 66.199997
14 0.733152 66.400002
15 0.759434 66.680000
16 0.784502 66.959999
17 0.759477 67.239998
18 0.625587 67.519997
19 0.639356 67.800003
20 0.638411 68.099998
21 0.637698 68.400002
22 0.683592 68.699997
23 0.686365 69.000000
24 0.710115 69.300003
25 NaN 64.500000
26 0.810234 64.660004
27 0.839397 64.820000
28 0.818189 65.139999
29 0.748588 65.500000
30 0.806754 65.699997
31 0.798651 65.900002
32 0.803259 66.099998
33 0.723094 52.500000
34 0.752593 53.200001
35 0.721591 53.900002
36 0.754615 54.599998
37 0.938463 66.820000
38 0.862206 66.940002
39 0.892195 67.059998
40 0.918693 67.180000
41 0.926799 67.300003
42 0.889073 67.480003
43 0.901776 67.660004
44 0.909874 67.839996
45 0.917870 68.019997
46 0.926492 68.199997
47 0.882819 68.400002
48 0.906699 68.599998
49 0.899912 68.800003
50 0.896371 69.000000
51 0.897104 69.199997
52 0.681877 64.800003
53 0.759644 64.900002
54 0.709486 65.000000
55 0.680007 65.099998
56 0.660342 65.199997
57 0.705108 65.360001
58 0.676446 65.519997
59 0.723260 65.680000
60 0.738764 65.839996
61 0.722551 66.000000
62 0.709218 66.300003
63 0.697925 66.599998
64 0.814449 66.900002
65 0.781604 67.199997
66 0.967892 71.400002
67 0.965276 71.720001
68 0.946635 71.879997
69 0.954520 72.199997
70 0.967029 72.300003
71 0.944599 72.400002
72 0.928205 72.500000
73 0.923799 72.599998
74 0.951862 72.699997
75 0.942334 73.000000
76 0.949958 73.300003
77 0.940137 73.599998
78 0.942774 73.900002
79 0.936517 74.199997
80 0.936350 70.760002
81 0.934593 71.080002
82 0.914193 71.400002
83 0.944157 71.540001
84 0.945142 71.680000
85 0.949809 71.820000
86 0.898920 71.959999
87 0.928110 72.099998
88 0.926319 72.400002
89 0.906218 72.699997
90 0.911668 73.000000
91 0.964489 73.300003
92 0.924831 73.599998
93 0.854415 61.880001
94 0.753247 62.259998
95 0.684267 62.639999
96 0.735970 63.020000
97 0.687001 63.400002
98 0.725194 63.639999
99 0.761873 63.880001
100 0.769690 64.120003
101 0.799433 64.360001
102 0.785703 64.599998
103 0.777271 64.900002
104 0.787039 65.199997
105 0.781230 65.500000
106 0.886756 65.800003
107 0.904143 65.940002
108 0.877115 66.300003
109 0.907868 66.580002
110 0.911350 66.860001
111 0.883781 67.139999
112 NaN 67.419998
113 0.852551 67.699997
114 0.862700 68.099998
115 0.875747 68.500000
116 0.877929 69.300003
117 0.847745 69.699997
118 0.672002 59.020000
119 0.514171 59.439999
120 0.466553 59.860001
121 0.527814 60.279999
122 0.549398 60.700001
123 0.606459 61.119999
124 0.581765 61.540001
125 0.530140 61.959999
126 0.577065 62.380001
127 0.601468 62.799999
128 0.649117 63.299999
129 0.712553 63.799999
130 0.705556 64.300003
131 0.673172 64.800003
132 0.739338 65.300003
133 0.917899 61.099998
134 0.857528 61.400002
135 0.903700 61.700001
136 0.907778 62.000000
137 0.918000 62.299999
138 0.909888 62.880001
139 0.901962 63.459999
140 0.922506 64.040001
141 0.880259 64.620003
142 0.924073 65.199997
143 0.926551 65.500000
144 0.900256 65.800003
145 0.904569 66.099998
146 0.916740 66.400002
147 0.934875 69.900002
148 0.921603 70.260002
149 0.922977 70.440002
150 0.930570 70.800003
151 0.936955 70.919998
152 0.927117 71.040001
153 0.909186 71.160004
154 0.943549 71.279999
155 0.885209 71.400002
156 0.928964 71.599998
157 0.921639 71.800003
158 0.929816 72.000000
159 0.884230 72.199997
160 0.903559 72.400002
161 0.872267 61.599998
162 0.756932 62.220001
163 0.444781 50.099998
164 0.382374 50.900002
165 0.477494 51.980000
166 0.523027 52.259998
167 0.576823 52.540001
168 0.506091 52.820000
169 0.434389 53.099998
170 0.492816 53.500000
171 0.435879 53.900002
172 0.503544 54.299999
173 0.442154 54.700001
174 0.506636 55.099998
175 0.818949 59.599998
176 0.880342 59.900002
177 0.847574 60.200001
178 0.834280 59.000000
179 0.796136 59.500000
180 0.785262 60.000000
181 0.831320 60.500000
182 0.807186 61.000000
183 0.816783 61.340000
184 0.780819 61.680000
185 0.802738 62.020000
186 0.821345 62.360001
187 0.828706 62.700001
188 0.795959 63.000000
189 0.778662 63.299999
190 0.827159 63.599998
191 0.784301 63.900002
192 0.804811 64.199997
193 0.765604 66.040001
194 0.735232 66.480003
195 0.772754 66.699997
196 0.725243 66.739998
197 0.778860 66.779999
198 0.766828 66.820000
199 0.787652 66.860001
200 0.655724 66.900002
201 0.807705 67.199997
202 0.775295 67.500000
203 0.835890 67.800003
204 0.873142 68.099998
205 0.898519 68.400002
206 0.883036 46.820000
207 0.831905 49.860001
208 0.865625 52.900002
209 0.860028 53.680000
210 0.836743 54.459999
211 0.855571 55.240002
212 0.859478 56.020000
213 0.815656 56.799999
214 0.768303 57.500000
215 0.768259 58.200001
216 0.794936 58.900002
217 0.773667 59.599998
218 0.882923 63.299999
219 0.886402 63.779999
220 0.878108 64.019997
221 0.912818 64.260002
222 0.905528 64.500000
223 0.916253 64.760002
224 0.890314 65.019997
225 0.910422 65.279999
226 0.898316 65.540001
227 0.906693 65.800003
228 0.912455 66.000000
229 0.904694 66.199997
230 0.881505 66.400002
231 0.899175 66.599998
232 0.830832 66.800003
233 0.831508 65.099998
234 0.843272 65.699997
235 0.860272 65.800003
236 0.837967 65.900002
237 0.829132 66.000000
238 0.885949 66.099998
239 0.907517 66.199997
240 0.926036 66.400002
241 0.941755 66.599998
242 0.923853 66.800003
243 0.948204 67.000000
244 0.916242 67.199997
245 0.796405 46.660000
246 0.770785 47.419998
247 0.726651 48.180000
248 0.773104 49.700001
249 0.709528 50.240002
250 0.743766 50.779999
251 0.745217 51.320000
252 0.742262 51.860001
253 0.705393 52.400002
254 0.764401 52.900002
255 0.784761 53.400002
256 0.664859 53.900002
257 0.683102 54.400002
258 0.290934 49.020000
259 0.325693 49.660000
260 0.422240 50.680000
261 0.564678 51.820000
262 0.484715 53.400002
263 0.793081 55.299999
264 0.675132 56.099998
265 0.619264 56.900002
266 0.818258 57.700001
267 0.697164 58.500000
268 0.715519 58.880001
269 0.605529 59.259998
270 0.650590 59.639999
271 0.693434 60.020000
272 0.728610 60.400002
273 0.745901 60.799999
274 0.765095 61.200001
275 0.794605 61.599998
276 0.759175 62.000000
277 0.724423 62.400002
278 0.689601 45.980000
279 0.717394 46.560001
280 0.696716 47.139999
281 0.728694 47.720001
282 0.758641 48.299999
283 0.737993 48.700001
284 0.742837 49.099998
285 0.760194 49.500000
286 0.777777 49.900002
287 0.646312 50.299999
288 0.659300 51.099998
289 0.694596 51.900002
290 0.676825 52.700001
291 0.710965 53.500000
292 0.720047 54.299999
293 0.961552 71.300003
294 NaN 71.660004
295 0.938707 71.839996
296 0.942845 72.019997
297 0.953765 72.199997
298 0.921669 72.360001
299 0.948128 72.519997
300 0.936239 72.680000
301 0.917836 72.839996
302 0.939067 73.000000
303 0.924393 73.199997
304 0.933749 73.400002
305 0.922719 73.599998
306 0.925304 73.800003
307 0.930611 74.000000
308 0.532297 40.900002
309 0.483334 42.700001
310 0.387391 43.080002
311 0.290184 44.900002
312 0.319589 45.200001
313 0.724308 43.180000
314 0.478951 43.660000
315 0.570835 44.139999
316 0.645714 44.619999
317 0.733714 45.099998
318 0.818844 45.419998
319 0.672866 45.740002
320 0.714145 46.060001
321 0.733067 46.380001
322 0.751252 46.700001
323 0.616205 47.200001
324 0.660616 47.700001
325 0.577254 48.200001
326 0.640452 48.700001
327 0.835544 68.660004
328 0.814621 68.720001
329 0.803759 68.779999
330 0.831582 68.839996
331 0.856955 68.900002
332 0.819079 69.040001
333 0.855236 69.180000
334 0.862405 69.320000
335 0.861552 69.459999
336 0.827142 69.599998
337 0.841388 69.699997
338 0.879841 69.800003
339 0.890085 69.900002
340 0.869122 70.000000
341 0.888412 70.099998
342 0.747011 66.879997
343 0.810852 67.059998
344 0.748287 67.239998
345 0.798034 67.419998
346 0.767753 67.599998
347 0.787171 67.760002
348 0.787818 67.919998
349 0.777896 68.080002
350 0.820366 68.239998
351 0.793734 68.400002
352 0.741703 68.699997
353 0.772033 69.000000
354 0.787605 69.300003
355 0.821936 69.599998
356 0.808334 69.900002
357 0.910293 65.220001
358 0.893707 65.339996
359 0.880067 65.459999
360 0.885927 65.580002
361 0.892993 65.699997
362 0.904147 65.919998
363 0.914373 66.139999
364 0.900778 66.360001
365 0.907403 66.580002
366 0.889900 66.800003
367 0.881900 67.099998
368 0.909250 67.400002
369 0.870970 67.699997
370 0.872579 68.000000
371 0.797035 68.300003
372 0.629427 54.360001
373 0.721343 54.700001
374 0.721833 55.020000
375 0.719218 55.340000
376 0.621303 57.200001
377 0.632013 57.500000
378 0.554772 52.200001
379 0.637118 54.580002
380 0.622330 54.959999
381 0.679935 55.340000
382 0.685935 55.720001
383 0.642136 56.099998
384 0.615449 56.700001
385 0.655441 57.299999
386 0.620623 57.900002
387 0.624768 58.500000
388 0.733060 49.340000
389 0.743947 50.340000
390 0.769546 50.779999
391 0.829852 51.220001
392 0.822286 51.660000
393 0.767236 52.099998
394 0.864155 52.500000
395 0.669688 52.900002
396 0.936938 69.940002
397 0.917678 69.879997
398 0.915759 69.820000
399 0.899782 69.760002
400 0.915141 69.699997
401 0.892048 69.900002
402 0.902207 70.099998
403 0.902069 70.300003
404 0.914211 70.500000
405 0.878273 70.699997
406 0.900701 70.900002
407 0.921697 71.099998
408 0.875872 71.300003
409 0.906077 71.500000
410 0.909822 67.120003
411 0.860663 67.639999
412 0.796392 67.900002
413 0.789739 68.000000
414 0.775818 68.099998
415 0.751262 68.199997
416 0.645698 68.300003
417 0.768363 68.400002
418 0.798332 69.000000
419 0.770310 69.599998
420 0.909807 70.199997
421 0.935989 70.800003
422 0.922913 71.400002
423 0.969595 68.440002
424 0.878201 71.440002
425 0.811736 72.160004
426 0.822124 72.400002
427 0.843655 72.540001
428 0.767177 72.680000
429 0.744032 72.820000
430 0.770176 72.959999
431 0.769556 73.099998
432 0.786438 73.300003
433 0.818671 73.500000
434 0.825573 73.699997
435 0.776078 73.900002
436 0.805559 74.099998
437 0.918759 67.000000
438 0.899779 67.440002
439 0.934161 68.099998
440 0.913511 68.239998
441 0.912427 68.379997
442 0.888043 68.519997
443 0.877915 68.660004
444 0.911363 68.800003
445 0.930593 69.300003
446 0.900969 69.800003
447 0.929164 70.300003
448 0.964054 71.300003
449 0.972372 69.599998
450 0.954201 69.919998
451 0.953912 70.080002
452 0.938892 70.239998
453 0.974977 70.400002
454 0.961736 70.620003
455 0.951437 70.839996
456 0.964708 71.059998
457 0.956344 71.279999
458 0.959701 71.500000
459 0.954452 71.800003
460 0.952100 72.099998
461 0.958219 72.400002
462 0.957706 72.699997
463 0.947371 73.000000
464 0.690440 53.259998
465 0.900565 53.779999
466 NaN 54.299999
467 0.632973 54.700001
468 0.918899 62.680000
469 0.847545 62.959999
470 0.850137 63.240002
471 0.878161 63.520000
472 0.859969 63.799999
473 0.872086 64.019997
474 0.879158 64.239998
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1768 0.923846 59.439999
1769 0.964419 60.040001
1770 0.945841 60.279999
1771 0.845733 60.520000
1772 0.908927 60.759998
1773 0.960158 61.000000
1774 0.929032 61.400002
1775 0.908455 61.799999
1776 0.984489 62.200001
1777 0.981502 62.599998
1778 0.760256 46.480000
1779 0.844879 47.459999
1780 0.812828 48.439999
1781 0.852087 49.419998
1782 0.830155 50.400002
1783 0.881751 51.220001
1784 0.884722 52.040001
1785 0.878275 52.860001
1786 0.821206 53.680000
1787 0.746633 54.500000
1788 0.753540 54.900002
1789 0.739956 55.299999
1790 0.739841 55.700001
1791 0.805487 56.099998
1792 0.800461 56.500000
1793 0.852453 60.119999
1794 0.820094 60.639999
1795 0.860014 61.160000
1796 0.845293 61.680000
1797 0.883555 62.200001
1798 0.859459 62.500000
1799 0.897573 62.799999
1800 0.896510 63.099998
1801 0.876760 63.400002
1802 0.909440 63.700001
1803 0.884961 64.000000
1804 0.858325 64.300003
1805 0.900937 64.599998
1806 0.882726 64.900002
1807 0.884686 65.199997
1808 0.903410 65.919998
1809 0.885089 66.279999
1810 0.911762 66.400002
1811 0.881369 66.419998
1812 0.855877 66.440002
1813 0.863716 66.459999
1814 NaN 66.480003
1815 0.824137 66.500000
1816 0.849380 66.699997
1817 0.835527 66.900002
1818 0.851041 67.099998
1819 0.861533 67.300003
1820 0.826756 67.500000
1821 0.978840 69.900002
1822 0.969870 70.459999
1823 0.953839 70.739998
1824 0.964429 71.019997
1825 0.955068 71.300003
1826 0.948711 71.379997
1827 0.934575 71.459999
1828 0.936884 71.540001
1829 0.910247 71.620003
1830 0.935986 71.699997
1831 0.954068 71.900002
1832 0.937495 72.099998
1833 0.928484 72.300003
1834 0.942681 72.500000
1835 0.929353 72.699997
1836 0.964572 68.059998
1837 NaN 68.220001
1838 0.952587 68.379997
1839 0.911794 68.540001
1840 0.926159 68.699997
1841 0.921705 68.680000
1842 0.903192 68.660004
1843 0.925397 68.639999
1844 0.902097 68.620003
1845 0.903571 68.599998
1846 0.896751 68.500000
1847 0.921003 68.400002
1848 0.903856 68.300003
1849 0.916691 68.199997
1850 0.937370 68.099998
1851 0.911877 67.440002
1852 0.874577 67.580002
1853 0.879114 67.720001
1854 0.923861 67.860001
1855 0.893040 68.000000
1856 0.891282 68.139999
1857 0.864694 68.279999
1858 0.917280 68.419998
1859 0.901898 68.559998
1860 0.891493 68.699997
1861 0.900381 68.800003
1862 0.913802 68.900002
1863 0.917316 69.000000
1864 0.933471 69.099998
1865 0.921070 69.199997
1866 0.903067 61.439999
1867 0.894026 62.320000
1868 0.904678 62.759998
1869 0.903226 63.200001
1870 0.924071 63.400002
1871 0.933141 63.599998
1872 0.962781 63.799999
1873 0.952406 64.000000
1874 0.968225 64.199997
1875 0.945102 64.500000
1876 0.942131 64.800003
1877 0.920821 65.099998
1878 0.915276 65.400002
1879 0.955278 65.400002
1880 0.946310 65.459999
1881 0.922434 65.580002
1882 0.944541 65.639999
1883 0.931576 65.699997
1884 0.930620 65.739998
1885 0.931630 65.779999
1886 0.896301 65.820000
1887 0.903956 65.860001
1888 0.911087 65.900002
1889 0.901949 66.099998
1890 0.895879 66.300003
1891 0.886882 66.500000
1892 0.887672 66.699997
1893 0.805224 66.900002
1894 0.887664 65.860001
1895 0.856023 66.019997
1896 0.804560 66.180000
1897 0.815026 66.339996
1898 0.786611 66.500000
1899 0.897655 66.660004
1900 0.775009 66.820000
1901 0.759477 66.980003
1902 0.792168 67.139999
1903 0.848677 67.300003
1904 0.876324 67.500000
1905 NaN 67.699997
1906 0.831945 67.900002
1907 0.847592 68.099998
1908 0.824969 53.400002
1909 0.756430 54.000000
1910 0.726612 54.299999
1911 0.662680 54.299999
1912 0.681678 54.299999
1913 0.693905 54.299999
1914 0.638252 54.299999
1915 0.668683 54.299999
1916 0.775407 55.099998
1917 0.789555 55.900002
1918 0.789422 56.700001
1919 0.870043 57.500000
1920 0.797665 44.259998
1921 0.687989 45.720001
1922 0.624418 47.180000
1923 0.781926 48.639999
1924 0.864023 50.840000
1925 0.780023 51.580002
1926 0.761312 52.320000
1927 0.706223 53.060001
1928 0.691483 53.799999
1929 0.767047 54.299999
1930 0.743754 54.799999
1931 0.717720 55.299999
1932 0.637894 55.799999
1933 0.766872 56.299999
1934 0.821656 41.580002
1935 0.828113 42.860001
1936 0.843475 44.139999
1937 0.805781 45.419998
1938 0.856638 46.700001
1939 0.864694 48.119999
1940 0.896476 49.540001
1941 0.799274 50.959999
1942 0.765839 52.380001
1943 0.735800 53.799999
1944 0.768425 54.400002
1945 0.754147 55.000000
1946 0.775388 55.599998
1947 0.759162 56.200001
1948 0.717243 56.799999
Freedom to make life choices Generosity Perceptions of corruption \
0 0.718114 0.167640 0.881686
1 0.678896 0.190099 0.850035
2 0.600127 0.120590 0.706766
3 0.495901 0.162427 0.731109
4 0.530935 0.236032 0.775620
5 0.577955 0.061148 0.823204
6 0.508514 0.104013 0.871242
7 0.388928 0.079864 0.880638
8 0.522566 0.042265 0.793246
9 0.427011 -0.121303 0.954393
10 0.373536 -0.093828 0.927606
11 0.393656 -0.108459 0.923849
12 0.528605 -0.008999 0.874700
13 0.525223 -0.157725 0.863665
14 0.568958 -0.172107 0.726262
15 0.487496 -0.204594 0.877003
16 0.601512 -0.168862 0.847675
17 0.631830 -0.127210 0.862905
18 0.734648 -0.024666 0.882704
19 0.703851 -0.080839 0.884793
20 0.729819 -0.016982 0.901071
21 0.749611 -0.028791 0.876135
22 0.824212 0.008912 0.899129
23 0.777351 -0.099263 0.914284
24 0.753671 0.006968 0.891359
25 0.592696 -0.205320 0.618038
26 0.529561 -0.180654 0.637982
27 0.586663 -0.172123 0.690116
28 NaN NaN NaN
29 NaN NaN NaN
30 0.436670 -0.166782 0.699774
31 0.583381 -0.145943 0.758704
32 0.385083 0.005087 0.740609
33 0.583702 0.055257 0.911320
34 0.456029 -0.136070 0.906300
35 0.409555 -0.103557 0.816375
36 0.374542 -0.167723 0.834076
37 0.733004 -0.156675 0.851799
38 0.652833 -0.140777 0.881058
39 0.678222 -0.131532 0.864996
40 0.636646 -0.129735 0.884742
41 0.730258 -0.125682 0.854695
42 0.815802 -0.173993 0.754646
43 0.747498 -0.147609 0.816546
44 0.737250 -0.130118 0.822900
45 0.745058 -0.164154 0.854192
46 0.881224 -0.173848 0.850906
47 0.847702 -0.191756 0.850924
48 0.831966 -0.185805 0.841052
49 0.845895 -0.210507 0.855255
50 0.817053 -0.210719 0.830460
51 0.823392 -0.122354 0.815780
52 0.520198 -0.231024 0.849513
53 0.605411 -0.251157 0.817445
54 0.462157 -0.215314 0.876099
55 0.441413 -0.214106 0.881887
56 0.459257 -0.176145 0.890629
57 0.464525 -0.225479 0.874601
58 0.501864 -0.215200 0.892544
59 0.504082 -0.195492 0.899797
60 0.506487 -0.218481 0.920390
61 0.551027 -0.202627 0.901462
62 0.610987 -0.170423 0.921421
63 0.613697 -0.146842 0.864683
64 0.807644 -0.162588 0.676826
65 0.844324 -0.172369 0.583473
66 0.934973 NaN 0.390416
67 0.890682 0.347052 0.512578
68 0.915733 0.305290 0.430811
69 0.932059 0.316744 0.366127
70 0.944586 0.369340 0.381772
71 0.935146 0.273635 0.368252
72 0.933379 0.268784 0.431539
73 0.922932 0.318556 0.442021
74 0.921871 0.331899 0.356554
75 0.922316 0.238558 0.398545
76 0.910550 0.317330 0.411347
77 0.916028 0.146455 0.404647
78 0.917537 0.120682 0.430209
79 0.905283 0.210030 0.491095
80 0.941382 0.302386 0.490111
81 0.879069 0.291309 0.613625
82 0.895980 0.130891 0.546145
83 0.939356 0.131578 0.702721
84 0.919704 0.117804 0.770586
85 0.921734 0.168248 0.678937
86 0.885027 0.117607 0.566931
87 0.900305 0.098893 0.557480
88 0.888514 0.079749 0.523641
89 0.890031 0.133064 0.518304
90 0.904112 0.053470 0.523061
91 0.903428 0.059686 0.457089
92 0.911910 0.011032 0.463830
93 0.771528 -0.234837 0.774117
94 0.522046 -0.206899 0.870910
95 0.601043 -0.029469 0.715125
96 0.498138 -0.086897 0.753850
97 0.501071 -0.123218 0.858347
98 0.537484 -0.104529 0.795119
99 0.598859 -0.139939 0.763155
100 0.671957 -0.167769 0.698820
101 0.732773 -0.208170 0.653845
102 0.764289 -0.197727 0.615553
103 0.712573 -0.204162 0.606771
104 0.731030 -0.225129 0.652539
105 0.772449 -0.231613 0.561206
106 0.854249 -0.214163 0.457261
107 0.895931 0.037422 0.506104
108 0.862003 -0.000584 0.714620
109 0.869870 -0.051371 0.582522
110 0.681823 NaN 0.437915
111 0.809206 NaN 0.524703
112 NaN NaN NaN
113 0.849521 0.112021 NaN
114 0.888691 0.088187 NaN
115 0.905859 0.136318 NaN
116 0.906536 0.047863 NaN
117 0.945233 0.132441 NaN
118 0.611664 0.068273 0.785916
119 0.604538 0.040335 0.806117
120 0.606012 -0.043634 0.801820
121 0.630931 -0.074515 0.776004
122 0.659006 -0.016196 0.773530
123 0.837995 -0.069335 0.757003
124 0.667682 -0.034349 0.764894
125 0.741518 -0.015539 0.742774
126 0.735513 -0.098169 0.789375
127 0.814796 -0.068449 0.720601
128 0.874700 -0.088731 0.687854
129 0.896217 0.011620 0.635014
130 0.901471 -0.043335 0.701421
131 0.901937 -0.051466 0.656005
132 0.777467 -0.008851 0.741659
133 0.707080 -0.246003 0.708275
134 0.667300 -0.224807 0.694849
135 0.639924 -0.220034 0.696496
136 0.679293 -0.202994 0.675543
137 0.700064 -0.162565 0.706121
138 0.656011 -0.167933 0.671939
139 0.645249 -0.217269 0.657430
140 0.723431 -0.177454 0.653039
141 0.647185 -0.048226 0.681509
142 0.622753 -0.091338 0.668678
143 0.658229 -0.125487 0.664055
144 0.620979 -0.121549 0.654113
145 0.643602 -0.174485 0.718455
146 0.656934 -0.185933 0.545905
147 0.923843 NaN 0.597554
148 0.900870 0.069500 0.721093
149 0.887027 0.006973 0.651801
150 0.806930 0.022295 0.697366
151 0.880154 -0.014154 0.711044
152 0.855267 -0.050071 0.757573
153 0.890711 0.016690 0.573664
154 0.860954 0.001345 0.511976
155 0.869475 0.062215 0.468785
156 0.865759 -0.055826 0.496659
157 0.856802 0.054314 0.543046
158 0.808387 -0.124600 0.630412
159 0.776204 -0.171521 0.672498
160 0.766918 -0.163784 0.633627
161 0.705306 0.032754 0.768984
162 0.873569 0.021996 0.782105
163 0.580069 -0.011183 0.789862
164 0.709477 -0.004316 0.825246
165 0.772919 -0.142235 0.849472
166 0.768971 -0.111311 0.805978
167 0.783240 -0.084775 0.855956
168 0.775546 -0.095703 0.854827
169 0.733384 -0.026638 0.850098
170 0.779795 -0.065072 0.837716
171 0.726808 -0.064986 0.767235
172 0.713264 0.002149 0.746511
173 0.770360 -0.016129 0.698347
174 0.783115 -0.083489 0.531884
175 0.810201 0.352631 0.802428
176 0.834222 0.267873 0.650338
177 0.830102 0.277412 0.633956
178 0.770135 -0.044180 0.794484
179 0.779935 0.000676 0.816994
180 0.725620 -0.091705 0.801420
181 0.778939 -0.036097 0.762605
182 0.703341 -0.068468 0.781343
183 0.781674 -0.039204 0.824854
184 0.862380 -0.014860 0.839701
185 0.845932 -0.066837 0.811857
186 0.881059 0.017844 0.831854
187 0.883625 -0.029515 0.862374
188 0.881749 -0.046750 0.852593
189 0.883905 -0.120381 0.819262
190 0.863247 -0.092877 0.786045
191 0.881311 -0.085674 0.857220
192 0.877032 -0.053764 0.868208
193 0.341566 0.005994 0.926125
194 0.257534 -0.025500 0.958740
195 0.364967 -0.127803 0.933030
196 0.333312 -0.034567 0.924784
197 0.419789 -0.012567 0.953422
198 0.390342 0.041853 0.969836
199 0.411937 0.231839 0.976340
200 0.630698 -0.054572 0.959854
201 0.633454 0.133866 0.957312
202 0.563799 0.091783 0.923343
203 0.658846 0.123263 0.912858
204 0.721563 0.079362 0.962908
205 0.740251 0.137954 0.916052
206 0.823775 -0.194722 0.723239
207 0.857776 -0.164389 0.806226
208 0.826219 -0.142860 0.813985
209 0.812514 -0.250003 0.816158
210 0.799410 -0.202824 0.814423
211 0.767357 -0.154177 0.748848
212 0.791371 -0.104892 0.743074
213 0.857169 -0.116254 0.860293
214 0.851695 -0.252724 0.729172
215 0.817308 -0.247892 0.731441
216 0.817621 -0.254148 0.806945
217 0.832543 -0.239001 0.792080
218 0.882186 NaN 0.744994
219 0.776645 -0.016235 0.728038
220 0.781931 -0.077661 0.688273
221 0.766716 -0.055252 0.722515
222 0.805949 -0.053969 0.656036
223 0.833656 -0.072337 0.662167
224 0.848606 NaN 0.622543
225 0.784815 -0.094682 0.706954
226 0.713814 -0.115171 0.710303
227 0.798935 -0.015562 0.771339
228 0.806572 -0.100316 0.781093
229 0.764793 -0.175128 0.794457
230 0.750609 -0.117002 0.763251
231 0.830206 -0.061973 0.761841
232 0.786235 -0.052820 0.728772
233 0.565787 -0.137790 0.976061
234 0.544536 -0.144253 0.940970
235 0.663528 -0.227830 0.947979
236 0.641256 -0.171941 0.938209
237 0.603213 -0.190944 0.962047
238 0.575596 -0.054812 0.954637
239 0.636818 -0.199828 0.941280
240 0.700266 -0.170193 0.935988
241 0.689047 -0.154141 0.910800
242 0.724336 -0.176177 0.952014
243 0.821930 -0.108587 0.942806
244 0.818225 -0.004322 0.900633
245 0.588338 0.028233 0.797701
246 0.582292 -0.060116 0.832765
247 0.612064 -0.100825 0.887124
248 0.586581 -0.036145 0.767335
249 0.724568 -0.104568 0.706798
250 0.621849 -0.069597 0.726287
251 0.741257 -0.015849 0.764721
252 0.709965 -0.003699 0.800758
253 0.659103 0.003571 0.692724
254 0.644682 -0.000543 0.720542
255 0.613775 -0.063232 0.727451
256 0.720743 -0.013175 0.757399
257 0.677547 -0.004090 0.729397
258 0.260069 -0.018894 0.859814
259 0.427356 -0.019278 0.718203
260 0.489863 -0.062434 0.677108
261 0.431385 -0.058800 0.807619
262 0.646399 -0.023876 0.598608
263 NaN 0.255207 0.829181
264 0.818700 0.115517 0.878508
265 0.914173 0.045451 0.888392
266 0.937233 0.152493 0.964779
267 0.940131 0.349865 0.895714
268 0.927462 0.418499 0.775356
269 0.955596 0.246725 0.890136
270 0.940593 0.163847 0.811992
271 0.937545 0.239398 0.842555
272 0.956320 0.210083 0.825130
273 0.957821 0.076060 0.840417
274 0.963775 0.087969 0.821023
275 0.958305 0.035572 NaN
276 0.956799 0.013223 0.828444
277 0.963075 0.052430 0.863054
278 0.653423 -0.009350 0.907068
279 0.643884 -0.031391 0.910350
280 0.580257 -0.068993 0.945003
281 0.698030 -0.016778 0.925447
282 0.792220 0.002303 0.874719
283 0.816694 -0.028886 0.869616
284 0.766064 -0.032058 0.898029
285 0.794076 -0.030284 0.867257
286 0.794646 -0.071320 0.855850
287 0.791429 0.049315 0.868049
288 0.712507 -0.003486 0.879451
289 0.766945 -0.028414 0.843586
290 0.816305 0.035603 0.884442
291 0.711500 -0.007858 0.817170
292 0.674509 0.049266 0.836517
293 0.957306 0.256230 0.502681
294 0.930341 0.249479 0.405608
295 0.926315 0.261585 0.369588
296 0.915058 0.246217 0.412622
297 0.933949 0.230451 0.412660
298 0.950925 0.253151 0.432992
299 0.917961 0.290013 0.465602
300 0.916014 0.315646 0.406236
301 0.938898 0.269858 0.441735
302 0.931469 0.252821 0.427152
303 0.912424 0.211162 0.385090
304 0.945145 0.162910 0.362034
305 0.945783 0.106098 0.371741
306 0.911526 0.111591 0.436434
307 0.886892 0.049637 0.434012
308 0.662871 0.081043 0.782131
309 0.689951 -0.035954 0.845377
310 0.780018 -0.015844 0.834499
311 0.624057 0.032623 0.859073
312 0.645252 0.072786 0.889566
313 0.306132 0.027806 0.961074
314 0.294612 -0.011461 0.873610
315 0.526610 0.062640 0.943554
316 0.401370 0.021430 0.931181
317 0.504613 0.024908 0.857664
318 0.540268 0.030600 0.876384
319 0.562908 -0.034040 0.884476
320 0.488210 -0.045458 0.881972
321 0.566795 -0.069863 0.880934
322 0.474361 -0.028660 0.888639
323 0.525222 0.052052 0.819789
324 0.614850 0.007875 0.792390
325 0.650355 0.024237 0.762879
326 0.537246 0.055001 0.832283
327 0.744292 0.168375 0.633630
328 0.661905 0.243907 0.722671
329 0.640202 0.083843 0.740667
330 0.746614 0.149212 0.734211
331 0.786367 0.107834 0.701825
332 0.700734 0.111660 0.752756
333 0.733611 0.195193 0.782117
334 0.736887 0.084833 0.741155
335 0.733326 0.217238 0.758498
336 0.768881 0.040594 0.811511
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1724 0.904828 0.258844 0.906596
1725 0.898245 0.308830 0.877040
1726 0.840463 0.273056 0.918340
1727 0.628228 -0.006546 0.849972
1728 0.286814 -0.054630 0.931986
1729 0.584088 -0.069823 0.832004
1730 0.663193 -0.084710 0.795342
1731 0.771577 -0.068682 0.733262
1732 0.730287 -0.006936 0.815044
1733 0.716694 -0.042179 0.725520
1734 0.611966 -0.006869 0.808538
1735 0.617420 0.064775 0.736675
1736 0.840089 0.141430 0.917428
1737 0.838140 0.086612 0.958828
1738 0.775392 0.077540 0.899957
1739 0.846941 0.127746 0.947674
1740 0.859140 0.014855 0.911336
1741 0.781496 -0.118570 0.722211
1742 0.623593 -0.135169 0.732379
1743 0.603124 -0.198725 0.912657
1744 0.567737 -0.176225 0.899453
1745 0.536288 -0.206911 0.886027
1746 0.588934 -0.231928 0.783134
1747 0.711373 -0.226031 0.814825
1748 0.614438 -0.164950 0.810746
1749 0.477957 -0.218600 0.868827
1750 0.649680 -0.191059 0.840117
1751 0.659332 -0.208865 0.888905
1752 0.667758 -0.201814 0.877354
1753 0.623115 NaN 0.876999
1754 0.459312 -0.178247 0.799733
1755 0.415498 -0.188817 0.785391
1756 0.455817 -0.227120 0.852887
1757 0.514920 -0.187196 0.810896
1758 0.445607 -0.241874 0.648596
1759 0.470903 -0.215605 0.701850
1760 0.540723 -0.229339 0.698065
1761 0.649196 -0.023702 0.764014
1762 0.653197 -0.016286 0.806076
1763 0.644147 -0.065029 0.763707
1764 0.644434 -0.237211 0.670911
1765 0.528629 -0.175576 0.804879
1766 0.631084 -0.135583 0.760442
1767 0.510386 -0.110889 0.774417
1768 NaN -0.101684 NaN
1769 NaN 0.018397 NaN
1770 0.785563 -0.122812 NaN
1771 0.704529 -0.071448 NaN
1772 0.804678 0.031971 NaN
1773 0.701358 0.092775 NaN
1774 0.748504 0.004624 NaN
1775 0.720399 0.066041 NaN
1776 0.857774 0.259659 NaN
1777 0.891527 0.284881 NaN
1778 0.746723 -0.041043 0.806589
1779 0.707961 -0.000834 0.880529
1780 0.577934 -0.054836 0.848459
1781 0.760231 -0.037409 0.840423
1782 0.800667 -0.014679 0.854992
1783 0.732974 0.031504 0.830124
1784 0.649463 0.081127 0.837546
1785 0.763021 0.052719 0.820481
1786 0.834174 0.009276 0.897995
1787 0.757835 0.135057 0.872740
1788 0.739410 0.131759 0.811070
1789 0.772344 0.059689 0.815770
1790 0.728513 0.078885 0.856106
1791 0.704377 0.138821 0.825613
1792 0.687482 0.147118 0.877587
1793 0.623814 -0.257109 0.929431
1794 0.493922 -0.240675 0.967940
1795 0.486627 -0.264713 0.929175
1796 0.460348 -0.241401 0.962244
1797 0.483833 -0.188660 0.953752
1798 0.578669 -0.227612 0.932535
1799 0.563650 -0.223113 0.896237
1800 0.568716 -0.216286 0.937324
1801 0.533267 0.083829 0.926789
1802 0.430592 -0.033402 0.952473
1803 0.502542 0.010513 0.891075
1804 0.598876 -0.002278 0.936764
1805 0.663055 -0.074371 0.942961
1806 0.715312 -0.081017 0.885005
1807 0.784273 0.126344 0.945669
1808 0.897557 -0.032504 0.203359
1809 0.848822 0.019040 0.338876
1810 0.877751 0.056747 0.355116
1811 0.889463 0.071289 NaN
1812 0.919793 NaN NaN
1813 0.935979 NaN NaN
1814 NaN NaN NaN
1815 0.915036 0.201111 NaN
1816 0.949120 0.131059 NaN
1817 0.962017 0.215843 NaN
1818 0.943664 0.053972 NaN
1819 0.911420 0.128725 NaN
1820 0.942162 0.060020 NaN
1821 0.922355 NaN 0.398457
1822 0.838332 0.336252 0.498093
1823 0.759144 0.331124 0.547769
1824 0.816229 0.341457 0.558927
1825 0.841307 0.403173 0.586813
1826 0.899774 0.336042 0.437595
1827 0.888970 0.371288 0.425170
1828 0.905278 0.346288 0.568043
1829 0.857040 0.354738 0.484118
1830 0.832926 0.300105 0.456134
1831 0.821192 0.250308 0.458313
1832 0.812733 0.291236 0.418611
1833 0.837508 0.226284 0.404276
1834 0.854040 0.270557 0.485092
1835 0.884624 0.202508 0.490204
1836 0.911496 NaN 0.600309
1837 0.871904 0.197084 0.633035
1838 0.877956 0.254692 0.668495
1839 0.830684 0.200643 0.665394
1840 0.828044 0.243921 0.689583
1841 0.863202 0.160684 0.696926
1842 0.822662 0.214699 0.710034
1843 0.792256 0.273915 0.746894
1844 0.866077 0.221340 0.702267
1845 0.848753 0.219460 0.697543
1846 0.757893 0.144048 0.738920
1847 0.868497 0.197317 0.681191
1848 0.824607 0.116116 0.709928
1849 0.836139 0.144299 0.706716
1850 0.850447 0.034103 0.678125
1851 0.806579 -0.112544 0.476627
1852 0.786249 -0.165002 0.614029
1853 0.807930 -0.142880 0.596767
1854 0.825049 -0.118288 0.543948
1855 0.832241 -0.158050 0.471376
1856 0.851442 -0.080015 0.556286
1857 0.870590 0.067105 0.615350
1858 0.888278 -0.043126 0.585632
1859 0.904333 -0.072777 0.533495
1860 0.916880 -0.032266 0.673476
1861 0.886372 -0.071944 0.676213
1862 0.897852 -0.091392 0.626582
1863 0.876211 -0.097156 0.682916
1864 0.902679 -0.095303 0.599400
1865 0.907762 -0.083987 0.491008
1866 0.784301 -0.115492 0.608808
1867 0.831269 -0.023097 NaN
1868 NaN 0.013131 0.610258
1869 NaN -0.030090 0.518720
1870 0.934133 0.042083 0.521862
1871 0.913550 -0.037380 0.463375
1872 0.949540 -0.034047 0.433932
1873 0.954481 0.061329 0.536461
1874 0.979937 0.374668 0.470917
1875 0.983803 0.208193 NaN
1876 0.985178 0.122524 0.464642
1877 0.969898 0.317585 0.520360
1878 0.970295 0.304298 0.511197
1879 0.838198 NaN 0.719800
1880 0.798281 -0.031057 0.646171
1881 0.678401 -0.225003 0.776103
1882 0.676886 -0.116365 0.827594
1883 0.768257 -0.154883 0.754269
1884 0.766335 -0.226387 0.771539
1885 0.804109 -0.192730 0.743374
1886 0.641965 -0.219742 0.837300
1887 0.569962 -0.198841 0.826535
1888 0.512159 -0.116937 0.813097
1889 0.457602 -0.154931 0.890125
1890 0.635505 -0.168757 0.843969
1891 0.610855 NaN 0.827560
1892 0.625526 NaN 0.839340
1893 0.611815 NaN 0.811319
1894 0.885792 0.014574 NaN
1895 0.917836 0.089205 0.753934
1896 0.888625 0.200575 0.789238
1897 0.834134 -0.061870 0.837870
1898 0.831494 -0.005769 0.742637
1899 0.818404 0.104993 0.742162
1900 0.856053 -0.110290 0.814885
1901 0.919607 -0.027052 0.771246
1902 NaN 0.000040 NaN
1903 NaN 0.085506 NaN
1904 0.894351 -0.089814 0.799240
1905 NaN NaN NaN
1906 0.909260 -0.040764 0.808423
1907 0.952469 -0.125531 0.787889
1908 0.672685 0.011009 NaN
1909 0.644229 -0.052247 0.832427
1910 0.659284 -0.104334 0.853403
1911 0.638211 -0.173486 0.753882
1912 0.705815 -0.170729 0.793233
1913 0.542547 -0.179008 0.885197
1914 0.663909 -0.157303 0.885429
1915 0.609981 -0.139383 0.829098
1916 0.532964 -0.150821 NaN
1917 0.595191 -0.146712 NaN
1918 0.552726 NaN 0.792587
1919 0.651308 NaN 0.798228
1920 0.720972 -0.005999 0.785281
1921 0.682005 -0.066975 0.947914
1922 0.716994 0.055702 0.890299
1923 0.696183 -0.095979 0.916553
1924 0.662850 0.002801 0.882150
1925 0.787760 0.007661 0.806394
1926 0.769912 -0.104419 0.732268
1927 0.811825 -0.010734 0.808841
1928 0.758654 -0.038819 0.871020
1929 0.811575 0.122350 0.770644
1930 0.823169 0.140323 0.739541
1931 0.790626 0.048121 0.810731
1932 0.811040 0.077462 0.831956
1933 0.750422 0.056029 0.809750
1934 0.431110 -0.076397 0.904757
1935 0.455957 -0.082092 0.946287
1936 0.343556 -0.089681 0.963846
1937 0.411089 -0.077691 0.930818
1938 0.664718 -0.092813 0.828361
1939 0.632978 -0.087876 0.829800
1940 0.469531 -0.102505 0.858691
1941 0.575884 -0.104101 0.830937
1942 0.642034 -0.073880 0.820217
1943 0.667193 -0.123171 0.810457
1944 0.732971 -0.094634 0.723612
1945 0.752826 -0.097645 0.751208
1946 0.762675 -0.068427 0.844209
1947 0.631908 -0.063791 0.830652
1948 0.643303 -0.008696 0.788523
Positive affect Negative affect
0 0.517637 0.258195
1 0.583926 0.237092
2 0.618265 0.275324
3 0.611387 0.267175
4 0.710385 0.267919
5 0.620585 0.273328
6 0.531691 0.374861
7 0.553553 0.339276
8 0.564953 0.348332
9 0.496349 0.371326
10 0.424125 0.404904
11 0.351387 0.502474
12 0.552678 0.246335
13 0.640024 0.279257
14 0.647908 0.300060
15 0.627659 0.256577
16 0.606636 0.271393
17 0.633609 0.338379
18 0.684911 0.334543
19 0.688370 0.350427
20 0.675244 0.321706
21 0.669241 0.333884
22 0.713300 0.318997
23 0.681080 0.273827
24 0.678661 0.265066
25 NaN NaN
26 0.550203 0.254897
27 0.604023 0.229716
28 0.625905 0.176866
29 0.660510 0.377112
30 0.641980 0.288710
31 0.591043 0.292946
32 0.584944 0.215198
33 0.658647 0.361063
34 0.557908 0.304890
35 0.658284 0.370875
36 0.578517 0.367864
37 0.824682 0.328230
38 0.827920 0.279008
39 0.823409 0.318222
40 0.863786 0.236901
41 0.846136 0.210975
42 0.840048 0.231855
43 0.856516 0.272219
44 0.842479 0.254205
45 0.857124 0.237913
46 0.858544 0.305355
47 0.841907 0.311646
48 0.809423 0.291717
49 0.820310 0.320502
50 0.825965 0.319055
51 0.763524 0.342497
52 0.494121 0.469419
53 0.507101 0.411717
54 0.520710 0.384892
55 0.542872 0.411280
56 0.509669 0.426496
57 0.474549 0.459074
58 0.517863 0.463855
59 0.562174 0.449950
60 0.580960 0.403984
61 0.594143 0.437948
62 0.593600 0.437228
63 0.625014 0.437149
64 0.581488 0.454840
65 0.598238 0.430463
66 0.842648 0.238012
67 0.826251 0.215351
68 0.826391 0.218427
69 0.834236 0.220073
70 0.815860 0.195324
71 0.810742 0.214397
72 0.818835 0.177142
73 0.775210 0.245304
74 0.790050 0.209637
75 0.790868 0.236086
76 0.780079 0.225361
77 0.759019 0.187456
78 0.770044 0.202190
79 0.769182 0.205078
80 0.823105 0.173812
81 0.832170 0.173195
82 0.814719 0.155793
83 0.789471 0.145238
84 0.822248 0.156675
85 0.787313 0.162603
86 0.779693 0.170150
87 0.798263 0.164469
88 0.755903 0.197424
89 0.747569 0.180269
90 0.752350 0.226059
91 0.774459 0.205170
92 0.769317 0.206500
93 0.511688 0.275695
94 0.520544 0.284357
95 0.577820 0.226795
96 0.543640 0.233942
97 0.526931 0.271873
98 0.535805 0.258117
99 0.553869 0.266093
100 0.618874 0.242455
101 0.597627 0.219982
102 0.606569 0.206114
103 0.597593 0.191117
104 0.592359 0.198319
105 0.592575 0.191392
106 0.642547 0.163920
107 0.763664 0.421889
108 0.684588 0.422671
109 0.543588 0.513719
110 0.589015 0.380815
111 0.768383 0.306209
112 NaN NaN
113 0.715543 0.302972
114 0.787187 0.283466
115 0.813571 0.289760
116 0.761623 0.317106
117 0.789795 0.296835
118 0.599945 0.320793
119 0.634599 0.313138
120 0.725387 0.231861
121 0.670300 0.223254
122 0.628580 0.292425
123 0.684994 0.234982
124 0.713508 0.183245
125 0.619046 0.246053
126 NaN 0.230678
127 0.634508 0.225754
128 0.559939 0.235022
129 0.568827 0.213506
130 0.541345 0.361238
131 0.537235 0.369472
132 0.582381 0.331709
133 0.605487 0.269400
134 0.595992 0.234981
135 NaN 0.245659
136 0.565597 0.223292
137 0.566530 0.208272
138 0.520890 0.249455
139 0.523195 0.180765
140 0.608714 0.206220
141 0.618929 0.208536
142 0.583727 0.184310
143 0.553870 0.182106
144 0.540906 0.232768
145 0.450333 0.235729
146 0.590851 0.189821
147 0.796279 0.260380
148 0.813477 0.217604
149 0.813123 0.241798
150 0.828259 0.240364
151 0.834545 0.225056
152 0.820486 0.238277
153 0.797417 0.217139
154 0.797634 0.251557
155 0.805178 0.239959
156 0.764590 0.259653
157 0.786368 0.233598
158 0.749563 0.250297
159 0.733456 0.243631
160 0.646510 0.260189
161 0.758783 0.250596
162 0.754977 0.281604
163 0.587210 0.309100
164 0.583623 0.302546
165 0.625820 0.218678
166 0.582524 0.230665
167 0.702019 0.216339
168 0.589645 0.273385
169 0.592222 0.373397
170 0.608237 0.455768
171 0.614722 0.457920
172 0.646655 0.467872
173 0.658774 0.441399
174 0.608585 0.304512
175 0.778723 0.217350
176 0.858864 0.324098
177 0.809641 0.311589
178 0.739243 0.431945
179 0.771075 0.387786
180 0.780654 0.392080
181 0.796764 0.372369
182 0.766100 0.349597
183 0.760786 0.361486
184 0.782481 0.408880
185 0.759099 0.410302
186 0.808609 0.398219
187 0.785768 0.392903
188 0.783009 0.376412
189 0.698195 0.433944
190 0.741973 0.387469
191 0.751408 0.419328
192 0.789818 0.381791
193 0.612804 0.296466
194 0.571649 0.390204
195 0.516695 0.409213
196 0.596073 0.325735
197 0.547963 0.338241
198 0.543630 0.314516
199 0.531436 0.262175
200 0.533987 0.286234
201 0.640764 0.304080
202 0.597342 0.270746
203 0.642940 0.277365
204 0.632990 0.238069
205 0.644237 0.325412
206 0.688109 0.225759
207 0.731180 0.217886
208 0.690273 0.172184
209 0.739315 0.159783
210 0.773364 0.171257
211 0.697809 0.243771
212 0.674190 0.245051
213 0.746204 0.261428
214 0.685667 0.251837
215 0.656396 0.276253
216 0.729643 0.267084
217 0.711796 0.272722
218 0.818337 0.301780
219 0.858976 0.299223
220 0.820272 0.265486
221 0.832505 0.274103
222 0.816655 0.249881
223 0.807467 0.267524
224 0.754625 0.349759
225 0.817662 0.275668
226 0.788230 0.273541
227 0.755194 0.324699
228 0.763112 0.302084
229 0.715945 0.307717
230 0.749728 0.349656
231 0.760846 0.337051
232 0.692024 0.389139
233 0.594433 0.226256
234 0.545824 0.237594
235 0.533738 0.270931
236 0.573091 0.236633
237 0.622750 0.278313
238 0.627810 0.235594
239 0.642794 0.214224
240 0.621855 0.171700
241 0.614217 0.188637
242 0.639022 0.189091
243 0.662825 0.199888
244 0.705835 0.221351
245 0.716253 0.265572
246 0.650698 0.280695
247 0.523474 0.303892
248 0.590039 0.216673
249 0.578625 0.204736
250 0.544851 0.299723
251 0.629771 0.286766
252 0.613732 0.255644
253 0.579356 0.359288
254 0.616067 0.337300
255 0.585172 0.353821
256 0.710884 0.342866
257 0.690926 0.364775
258 0.439698 0.252771
259 0.640622 0.163643
260 0.688907 0.190345
261 0.655664 0.251095
262 0.666442 0.362767
263 0.718541 0.341023
264 NaN 0.320335
265 0.739183 0.335324
266 0.796208 0.187687
267 0.774445 0.421966
268 0.799231 0.307869
269 0.820461 0.351859
270 0.791689 0.440312
271 0.783240 0.481934
272 0.812530 0.399103
273 0.838552 0.398200
274 0.798617 0.408284
275 0.844593 0.414346
276 0.844354 0.389586
277 0.877954 0.389852
278 0.605588 0.270874
279 0.634789 0.248631
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281 0.593139 0.249822
282 0.606357 0.273786
283 0.597826 0.271676
284 0.617999 0.284448
285 0.681132 0.268199
286 0.622733 0.216040
287 0.650875 0.346430
288 0.661523 0.367093
289 0.632339 0.377499
290 0.642437 0.355642
291 0.629451 0.326395
292 0.629615 0.386479
293 0.838544 0.233278
294 0.871604 0.256810
295 0.890220 0.202175
296 0.867433 0.247633
297 0.878868 0.233113
298 0.881385 0.247729
299 0.856704 0.229332
300 0.851297 0.262850
301 0.833404 0.258602
302 0.845328 0.286280
303 0.824586 0.237423
304 0.862773 0.217981
305 0.823669 0.259398
306 0.822443 0.284834
307 0.795949 0.306674
308 0.567980 0.329995
309 0.523006 0.256705
310 0.524068 0.277180
311 0.578654 0.494268
312 0.613865 0.599335
313 0.580500 0.262727
314 0.613522 0.245208
315 0.569130 0.225484
316 0.556809 0.221047
317 0.544883 0.287241
318 0.591423 0.289146
319 0.526546 0.315747
320 0.461591 0.314174
321 0.536371 0.328529
322 0.606683 0.358438
323 0.582458 0.467567
324 0.627503 0.538245
325 0.552737 0.543836
326 0.587211 0.460061
327 0.804136 0.347657
328 0.766979 0.342262
329 0.756524 0.329703
330 0.808314 0.299891
331 0.809173 0.300117
332 0.803743 0.316876
333 0.815391 0.287592
334 0.855062 0.285454
335 0.869811 0.276103
336 0.803025 0.332747
337 0.869229 0.283042
338 0.838475 0.291042
339 0.832562 0.275820
340 0.808617 0.337244
341 0.814603 0.336029
342 0.809295 0.169580
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1628 0.733572 0.244927
1629 0.668583 0.220789
1630 0.585826 0.248501
1631 0.576178 0.242374
1632 0.540845 0.302725
1633 0.764223 0.250365
1634 0.820613 0.251053
1635 0.824355 0.252339
1636 0.777627 0.279595
1637 0.839870 0.150766
1638 0.796209 0.177412
1639 0.804467 0.134403
1640 0.819678 0.151363
1641 0.833033 0.200112
1642 0.814561 0.179152
1643 0.855100 0.170226
1644 0.829284 0.184420
1645 0.835672 0.207688
1646 0.817942 0.190992
1647 0.815695 0.200607
1648 0.813548 0.175067
1649 0.822676 0.160755
1650 0.826284 0.202000
1651 0.766376 0.221933
1652 0.821402 0.211929
1653 0.814037 0.201585
1654 0.859107 0.176007
1655 0.822913 0.188794
1656 0.808529 0.165759
1657 0.779471 0.206317
1658 0.773997 0.195871
1659 0.792226 0.191520
1660 0.797893 0.170762
1661 0.768705 0.193229
1662 0.609097 0.338427
1663 0.574330 0.292455
1664 0.557652 0.224644
1665 0.598737 0.495505
1666 0.464439 0.704590
1667 0.386987 0.622230
1668 0.369440 0.642589
1669 0.813638 0.094316
1670 0.794352 0.169157
1671 0.845345 0.135867
1672 0.826713 0.112288
1673 0.821362 0.140011
1674 0.846232 0.124445
1675 0.848841 0.108366
1676 0.831987 0.129349
1677 0.833153 0.108305
1678 0.837277 0.114123
1679 0.848399 0.092696
1680 0.860071 0.093412
1681 0.845393 0.082737
1682 0.565764 0.194671
1683 0.694193 0.133114
1684 0.605863 0.160436
1685 0.605244 0.203190
1686 0.642683 0.191733
1687 0.697810 0.165632
1688 0.714460 0.198191
1689 0.676519 0.169621
1690 0.656047 0.196154
1691 0.688922 0.195661
1692 0.644485 0.219800
1693 0.602668 0.277725
1694 0.694633 0.219794
1695 0.728972 0.178497
1696 0.748898 0.344161
1697 0.748167 0.209238
1698 0.755214 0.219853
1699 0.744346 0.178047
1700 0.778500 0.160527
1701 0.716567 0.146119
1702 0.764551 0.145141
1703 0.678828 0.195307
1704 0.737968 0.191288
1705 0.730893 0.241431
1706 0.619377 0.191748
1707 0.693552 0.245986
1708 0.714646 0.255336
1709 0.762089 0.221005
1710 0.726239 0.243098
1711 0.685533 0.271118
1712 0.813509 0.164123
1713 0.831810 0.180010
1714 0.819038 0.145059
1715 0.897641 0.166086
1716 0.901268 0.181523
1717 0.934374 0.116676
1718 0.854544 0.137503
1719 0.845981 0.140831
1720 0.811370 0.168738
1721 0.910497 0.174081
1722 0.834758 0.217880
1723 0.816322 0.231598
1724 0.843489 0.198190
1725 0.842873 0.208184
1726 0.783270 0.326169
1727 0.614520 0.348205
1728 0.362498 0.378715
1729 0.480281 0.395363
1730 0.582750 0.442813
1731 0.598805 0.415781
1732 0.604244 0.482886
1733 0.614189 0.425824
1734 0.608449 0.446454
1735 0.590229 0.443870
1736 0.797640 0.229044
1737 0.817198 0.183790
1738 0.906178 0.134091
1739 0.832503 0.285929
1740 0.846467 0.248099
1741 NaN NaN
1742 0.724581 0.248913
1743 0.587680 0.248197
1744 0.520914 0.327000
1745 0.517319 0.239156
1746 0.502728 0.320770
1747 0.572956 0.319542
1748 0.612341 0.378108
1749 0.420962 0.377197
1750 0.591727 0.365014
1751 0.538935 0.433413
1752 0.584634 0.438774
1753 0.556581 NaN
1754 0.650955 0.395127
1755 0.614249 0.345338
1756 0.598295 0.316302
1757 0.651793 0.327066
1758 0.621293 0.379784
1759 0.644781 0.334833
1760 0.634615 0.391874
1761 0.483359 0.377325
1762 0.460246 0.382291
1763 0.465151 0.389963
1764 0.449801 0.312846
1765 0.434654 0.350773
1766 0.422227 0.368089
1767 0.384292 0.440387
1768 0.780770 0.151584
1769 0.639033 0.122068
1770 0.584448 0.116881
1771 0.598716 0.159606
1772 0.695216 0.153950
1773 0.705348 0.301039
1774 0.636389 0.255499
1775 0.520885 0.349628
1776 0.612210 0.189025
1777 0.509915 0.183343
1778 0.589651 0.254418
1779 0.708058 0.227878
1780 0.640577 0.239573
1781 0.640410 0.296116
1782 0.647654 0.251242
1783 0.678213 0.254482
1784 0.753984 0.265322
1785 0.675636 0.346357
1786 0.680730 0.396720
1787 0.702905 0.352848
1788 0.667976 0.410067
1789 0.703376 0.400026
1790 0.685169 0.390319
1791 0.693082 0.385221
1792 0.698949 0.424707
1793 0.621520 0.249234
1794 0.636170 0.207652
1795 0.573153 0.185806
1796 0.583073 0.189014
1797 0.512683 0.227200
1798 0.590430 0.219648
1799 0.570338 0.192819
1800 0.643462 0.224596
1801 0.594337 0.248560
1802 0.574076 0.241076
1803 0.588722 0.219624
1804 0.597112 0.234764
1805 0.608771 0.221851
1806 0.634228 0.201132
1807 0.687721 0.284736
1808 0.746001 0.275255
1809 0.770118 0.287074
1810 0.762652 0.233014
1811 0.762837 0.215870
1812 0.767661 0.223985
1813 NaN 0.291113
1814 NaN NaN
1815 0.760500 0.295733
1816 0.775128 0.244668
1817 0.795035 0.207598
1818 0.787243 0.302042
1819 0.793177 0.283763
1820 0.751660 0.298480
1821 0.864076 0.261732
1822 0.782353 0.241052
1823 0.818951 0.218297
1824 0.846380 0.231029
1825 0.862621 0.176343
1826 0.844498 0.173908
1827 0.844452 0.184245
1828 0.775744 0.252096
1829 0.793993 0.251140
1830 0.797785 0.219262
1831 0.775853 0.229587
1832 0.758572 0.209572
1833 0.783172 0.228276
1834 0.775203 0.251014
1835 0.758164 0.224655
1836 0.827417 0.260511
1837 0.828503 0.231679
1838 0.871968 0.226823
1839 0.843484 0.261661
1840 0.860642 0.231053
1841 0.836360 0.273379
1842 0.833771 0.259644
1843 0.813678 0.260328
1844 0.834294 0.281265
1845 0.813908 0.274688
1846 0.805674 0.264204
1847 0.826555 0.268269
1848 0.815383 0.292226
1849 0.814985 0.243834
1850 0.787372 0.295499
1851 0.784314 0.306158
1852 0.776779 0.273572
1853 0.751168 0.264006
1854 0.793431 0.254544
1855 0.806707 0.231179
1856 0.805346 0.252250
1857 0.787868 0.214203
1858 0.826393 0.253229
1859 0.869249 0.251499
1860 0.892661 0.299538
1861 0.841549 0.283180
1862 0.835861 0.280323
1863 0.876920 0.274946
1864 0.888966 0.221730
1865 0.807351 0.264692
1866 0.727946 0.195058
1867 0.713683 0.186682
1868 0.735559 0.158657
1869 0.775874 0.151883
1870 0.787154 0.122773
1871 0.785679 0.118177
1872 0.749193 0.130197
1873 0.804545 0.106158
1874 0.839981 0.103494
1875 0.841676 0.146898
1876 0.838989 0.202737
1877 0.825422 0.208660
1878 0.844809 0.219746
1879 0.819065 0.233014
1880 0.858956 0.178483
1881 0.801530 0.224191
1882 0.824885 0.180226
1883 0.861522 0.129686
1884 0.827956 0.198666
1885 0.857873 0.176308
1886 0.839730 0.237609
1887 0.810578 0.243604
1888 0.867409 0.222635
1889 0.688201 0.391754
1890 0.725643 0.362985
1891 0.759221 0.373658
1892 0.761240 0.350950
1893 0.722391 0.396250
1894 0.682261 0.203979
1895 0.587590 0.205932
1896 0.665097 0.217538
1897 0.582757 0.189930
1898 0.685243 0.215798
1899 0.531590 0.192669
1900 0.615128 0.221356
1901 0.718431 0.165225
1902 0.701386 0.240607
1903 0.642237 0.232416
1904 0.536226 0.222550
1905 NaN NaN
1906 0.692222 0.191061
1907 0.751160 0.185610
1908 0.591898 0.378784
1909 0.583224 0.374160
1910 0.582427 0.308333
1911 0.502691 0.284863
1912 0.501776 0.262817
1913 0.558500 0.265685
1914 0.610585 0.275674
1915 0.507435 0.321357
1916 0.469345 0.227925
1917 0.455182 0.295064
1918 0.461114 0.314870
1919 0.542806 0.213043
1920 0.700788 0.226278
1921 0.686748 0.245637
1922 0.744144 0.205723
1923 0.727505 0.122659
1924 0.833214 0.204070
1925 0.725965 0.250368
1926 0.734979 0.307960
1927 0.692035 0.327384
1928 0.690034 0.381731
1929 0.730680 0.372241
1930 0.684623 0.387189
1931 0.702698 0.350963
1932 0.743407 0.394385
1933 0.691082 0.344526
1934 0.715229 0.297147
1935 0.660861 0.264989
1936 0.630983 0.250060
1937 0.735503 0.218419
1938 0.747702 0.122150
1939 0.781189 0.210544
1940 0.669279 0.177311
1941 0.711885 0.182288
1942 0.725214 0.239111
1943 0.715079 0.178861
1944 0.737636 0.208555
1945 0.806428 0.224051
1946 0.710119 0.211726
1947 0.716004 0.235354
1948 0.702573 0.345736
happiness.rename(columns={'Country name': 'Country_name', 'Life Ladder': 'Life_ladder'}, inplace=True)
happiness
| Country_name | year | Life_ladder | Log GDP per capita | Social support | Healthy life expectancy at birth | Freedom to make life choices | Generosity | Perceptions of corruption | Positive affect | Negative affect | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | 2008 | 3.723590 | 7.370100 | 0.450662 | 50.799999 | 0.718114 | 0.167640 | 0.881686 | 0.517637 | 0.258195 |
| 1 | Afghanistan | 2009 | 4.401778 | 7.539972 | 0.552308 | 51.200001 | 0.678896 | 0.190099 | 0.850035 | 0.583926 | 0.237092 |
| 2 | Afghanistan | 2010 | 4.758381 | 7.646709 | 0.539075 | 51.599998 | 0.600127 | 0.120590 | 0.706766 | 0.618265 | 0.275324 |
| 3 | Afghanistan | 2011 | 3.831719 | 7.619532 | 0.521104 | 51.919998 | 0.495901 | 0.162427 | 0.731109 | 0.611387 | 0.267175 |
| 4 | Afghanistan | 2012 | 3.782938 | 7.705479 | 0.520637 | 52.240002 | 0.530935 | 0.236032 | 0.775620 | 0.710385 | 0.267919 |
| 5 | Afghanistan | 2013 | 3.572100 | 7.725029 | 0.483552 | 52.560001 | 0.577955 | 0.061148 | 0.823204 | 0.620585 | 0.273328 |
| 6 | Afghanistan | 2014 | 3.130896 | 7.718354 | 0.525568 | 52.880001 | 0.508514 | 0.104013 | 0.871242 | 0.531691 | 0.374861 |
| 7 | Afghanistan | 2015 | 3.982855 | 7.701992 | 0.528597 | 53.200001 | 0.388928 | 0.079864 | 0.880638 | 0.553553 | 0.339276 |
| 8 | Afghanistan | 2016 | 4.220169 | 7.696560 | 0.559072 | 53.000000 | 0.522566 | 0.042265 | 0.793246 | 0.564953 | 0.348332 |
| 9 | Afghanistan | 2017 | 2.661718 | 7.697381 | 0.490880 | 52.799999 | 0.427011 | -0.121303 | 0.954393 | 0.496349 | 0.371326 |
| 10 | Afghanistan | 2018 | 2.694303 | 7.691767 | 0.507516 | 52.599998 | 0.373536 | -0.093828 | 0.927606 | 0.424125 | 0.404904 |
| 11 | Afghanistan | 2019 | 2.375092 | 7.697248 | 0.419973 | 52.400002 | 0.393656 | -0.108459 | 0.923849 | 0.351387 | 0.502474 |
| 12 | Albania | 2007 | 4.634252 | 9.142183 | 0.821372 | 65.800003 | 0.528605 | -0.008999 | 0.874700 | 0.552678 | 0.246335 |
| 13 | Albania | 2009 | 5.485470 | 9.261868 | 0.833047 | 66.199997 | 0.525223 | -0.157725 | 0.863665 | 0.640024 | 0.279257 |
| 14 | Albania | 2010 | 5.268937 | 9.303230 | 0.733152 | 66.400002 | 0.568958 | -0.172107 | 0.726262 | 0.647908 | 0.300060 |
| 15 | Albania | 2011 | 5.867422 | 9.331056 | 0.759434 | 66.680000 | 0.487496 | -0.204594 | 0.877003 | 0.627659 | 0.256577 |
| 16 | Albania | 2012 | 5.510124 | 9.346783 | 0.784502 | 66.959999 | 0.601512 | -0.168862 | 0.847675 | 0.606636 | 0.271393 |
| 17 | Albania | 2013 | 4.550648 | 9.358584 | 0.759477 | 67.239998 | 0.631830 | -0.127210 | 0.862905 | 0.633609 | 0.338379 |
| 18 | Albania | 2014 | 4.813763 | 9.378244 | 0.625587 | 67.519997 | 0.734648 | -0.024666 | 0.882704 | 0.684911 | 0.334543 |
| 19 | Albania | 2015 | 4.606651 | 9.403102 | 0.639356 | 67.800003 | 0.703851 | -0.080839 | 0.884793 | 0.688370 | 0.350427 |
| 20 | Albania | 2016 | 4.511101 | 9.437311 | 0.638411 | 68.099998 | 0.729819 | -0.016982 | 0.901071 | 0.675244 | 0.321706 |
| 21 | Albania | 2017 | 4.639548 | 9.475548 | 0.637698 | 68.400002 | 0.749611 | -0.028791 | 0.876135 | 0.669241 | 0.333884 |
| 22 | Albania | 2018 | 5.004403 | 9.517920 | 0.683592 | 68.699997 | 0.824212 | 0.008912 | 0.899129 | 0.713300 | 0.318997 |
| 23 | Albania | 2019 | 4.995318 | 9.544080 | 0.686365 | 69.000000 | 0.777351 | -0.099263 | 0.914284 | 0.681080 | 0.273827 |
| 24 | Albania | 2020 | 5.364910 | 9.497252 | 0.710115 | 69.300003 | 0.753671 | 0.006968 | 0.891359 | 0.678661 | 0.265066 |
| 25 | Algeria | 2010 | 5.463567 | 9.286936 | NaN | 64.500000 | 0.592696 | -0.205320 | 0.618038 | NaN | NaN |
| 26 | Algeria | 2011 | 5.317194 | 9.296691 | 0.810234 | 64.660004 | 0.529561 | -0.180654 | 0.637982 | 0.550203 | 0.254897 |
| 27 | Algeria | 2012 | 5.604596 | 9.310611 | 0.839397 | 64.820000 | 0.586663 | -0.172123 | 0.690116 | 0.604023 | 0.229716 |
| 28 | Algeria | 2014 | 6.354898 | 9.335159 | 0.818189 | 65.139999 | NaN | NaN | NaN | 0.625905 | 0.176866 |
| 29 | Algeria | 2016 | 5.340854 | 9.362022 | 0.748588 | 65.500000 | NaN | NaN | NaN | 0.660510 | 0.377112 |
| 30 | Algeria | 2017 | 5.248912 | 9.354488 | 0.806754 | 65.699997 | 0.436670 | -0.166782 | 0.699774 | 0.641980 | 0.288710 |
| 31 | Algeria | 2018 | 5.043086 | 9.348318 | 0.798651 | 65.900002 | 0.583381 | -0.145943 | 0.758704 | 0.591043 | 0.292946 |
| 32 | Algeria | 2019 | 4.744627 | 9.336946 | 0.803259 | 66.099998 | 0.385083 | 0.005087 | 0.740609 | 0.584944 | 0.215198 |
| 33 | Angola | 2011 | 5.589001 | 8.945782 | 0.723094 | 52.500000 | 0.583702 | 0.055257 | 0.911320 | 0.658647 | 0.361063 |
| 34 | Angola | 2012 | 4.360250 | 8.991773 | 0.752593 | 53.200001 | 0.456029 | -0.136070 | 0.906300 | 0.557908 | 0.304890 |
| 35 | Angola | 2013 | 3.937107 | 9.004611 | 0.721591 | 53.900002 | 0.409555 | -0.103557 | 0.816375 | 0.658284 | 0.370875 |
| 36 | Angola | 2014 | 3.794838 | 9.016735 | 0.754615 | 54.599998 | 0.374542 | -0.167723 | 0.834076 | 0.578517 | 0.367864 |
| 37 | Argentina | 2006 | 6.312925 | 9.941642 | 0.938463 | 66.820000 | 0.733004 | -0.156675 | 0.851799 | 0.824682 | 0.328230 |
| 38 | Argentina | 2007 | 6.073158 | 10.017901 | 0.862206 | 66.940002 | 0.652833 | -0.140777 | 0.881058 | 0.827920 | 0.279008 |
| 39 | Argentina | 2008 | 5.961034 | 10.047747 | 0.892195 | 67.059998 | 0.678222 | -0.131532 | 0.864996 | 0.823409 | 0.318222 |
| 40 | Argentina | 2009 | 6.424133 | 9.976742 | 0.918693 | 67.180000 | 0.636646 | -0.129735 | 0.884742 | 0.863786 | 0.236901 |
| 41 | Argentina | 2010 | 6.441067 | 10.065669 | 0.926799 | 67.300003 | 0.730258 | -0.125682 | 0.854695 | 0.846136 | 0.210975 |
| 42 | Argentina | 2011 | 6.775805 | 10.112445 | 0.889073 | 67.480003 | 0.815802 | -0.173993 | 0.754646 | 0.840048 | 0.231855 |
| 43 | Argentina | 2012 | 6.468387 | 10.090758 | 0.901776 | 67.660004 | 0.747498 | -0.147609 | 0.816546 | 0.856516 | 0.272219 |
| 44 | Argentina | 2013 | 6.582260 | 10.103335 | 0.909874 | 67.839996 | 0.737250 | -0.130118 | 0.822900 | 0.842479 | 0.254205 |
| 45 | Argentina | 2014 | 6.671114 | 10.066894 | 0.917870 | 68.019997 | 0.745058 | -0.164154 | 0.854192 | 0.857124 | 0.237913 |
| 46 | Argentina | 2015 | 6.697131 | 10.083059 | 0.926492 | 68.199997 | 0.881224 | -0.173848 | 0.850906 | 0.858544 | 0.305355 |
| 47 | Argentina | 2016 | 6.427221 | 10.051465 | 0.882819 | 68.400002 | 0.847702 | -0.191756 | 0.850924 | 0.841907 | 0.311646 |
| 48 | Argentina | 2017 | 6.039330 | 10.067430 | 0.906699 | 68.599998 | 0.831966 | -0.185805 | 0.841052 | 0.809423 | 0.291717 |
| 49 | Argentina | 2018 | 5.792797 | 10.032141 | 0.899912 | 68.800003 | 0.845895 | -0.210507 | 0.855255 | 0.820310 | 0.320502 |
| 50 | Argentina | 2019 | 6.085561 | 10.000340 | 0.896371 | 69.000000 | 0.817053 | -0.210719 | 0.830460 | 0.825965 | 0.319055 |
| 51 | Argentina | 2020 | 5.900567 | 9.850450 | 0.897104 | 69.199997 | 0.823392 | -0.122354 | 0.815780 | 0.763524 | 0.342497 |
| 52 | Armenia | 2006 | 4.289311 | 9.043633 | 0.681877 | 64.800003 | 0.520198 | -0.231024 | 0.849513 | 0.494121 | 0.469419 |
| 53 | Armenia | 2007 | 4.881516 | 9.180747 | 0.759644 | 64.900002 | 0.605411 | -0.251157 | 0.817445 | 0.507101 | 0.411717 |
| 54 | Armenia | 2008 | 4.651972 | 9.256032 | 0.709486 | 65.000000 | 0.462157 | -0.215314 | 0.876099 | 0.520710 | 0.384892 |
| 55 | Armenia | 2009 | 4.177582 | 9.110784 | 0.680007 | 65.099998 | 0.441413 | -0.214106 | 0.881887 | 0.542872 | 0.411280 |
| 56 | Armenia | 2010 | 4.367811 | 9.136283 | 0.660342 | 65.199997 | 0.459257 | -0.176145 | 0.890629 | 0.509669 | 0.426496 |
| 57 | Armenia | 2011 | 4.260491 | 9.182483 | 0.705108 | 65.360001 | 0.464525 | -0.225479 | 0.874601 | 0.474549 | 0.459074 |
| 58 | Armenia | 2012 | 4.319712 | 9.249339 | 0.676446 | 65.519997 | 0.501864 | -0.215200 | 0.892544 | 0.517863 | 0.463855 |
| 59 | Armenia | 2013 | 4.277191 | 9.277186 | 0.723260 | 65.680000 | 0.504082 | -0.195492 | 0.899797 | 0.562174 | 0.449950 |
| 60 | Armenia | 2014 | 4.453083 | 9.307452 | 0.738764 | 65.839996 | 0.506487 | -0.218481 | 0.920390 | 0.580960 | 0.403984 |
| 61 | Armenia | 2015 | 4.348320 | 9.334446 | 0.722551 | 66.000000 | 0.551027 | -0.202627 | 0.901462 | 0.594143 | 0.437948 |
| 62 | Armenia | 2016 | 4.325472 | 9.332829 | 0.709218 | 66.300003 | 0.610987 | -0.170423 | 0.921421 | 0.593600 | 0.437228 |
| 63 | Armenia | 2017 | 4.287736 | 9.402205 | 0.697925 | 66.599998 | 0.613697 | -0.146842 | 0.864683 | 0.625014 | 0.437149 |
| 64 | Armenia | 2018 | 5.062449 | 9.450535 | 0.814449 | 66.900002 | 0.807644 | -0.162588 | 0.676826 | 0.581488 | 0.454840 |
| 65 | Armenia | 2019 | 5.488087 | 9.521770 | 0.781604 | 67.199997 | 0.844324 | -0.172369 | 0.583473 | 0.598238 | 0.430463 |
| 66 | Australia | 2005 | 7.340688 | 10.658608 | 0.967892 | 71.400002 | 0.934973 | NaN | 0.390416 | 0.842648 | 0.238012 |
| 67 | Australia | 2007 | 7.285391 | 10.702894 | 0.965276 | 71.720001 | 0.890682 | 0.347052 | 0.512578 | 0.826251 | 0.215351 |
| 68 | Australia | 2008 | 7.253757 | 10.718780 | 0.946635 | 71.879997 | 0.915733 | 0.305290 | 0.430811 | 0.826391 | 0.218427 |
| 69 | Australia | 2010 | 7.450047 | 10.722262 | 0.954520 | 72.199997 | 0.932059 | 0.316744 | 0.366127 | 0.834236 | 0.220073 |
| 70 | Australia | 2011 | 7.405616 | 10.732697 | 0.967029 | 72.300003 | 0.944586 | 0.369340 | 0.381772 | 0.815860 | 0.195324 |
| 71 | Australia | 2012 | 7.195586 | 10.753672 | 0.944599 | 72.400002 | 0.935146 | 0.273635 | 0.368252 | 0.810742 | 0.214397 |
| 72 | Australia | 2013 | 7.364169 | 10.761981 | 0.928205 | 72.500000 | 0.933379 | 0.268784 | 0.431539 | 0.818835 | 0.177142 |
| 73 | Australia | 2014 | 7.288550 | 10.772080 | 0.923799 | 72.599998 | 0.922932 | 0.318556 | 0.442021 | 0.775210 | 0.245304 |
| 74 | Australia | 2015 | 7.309061 | 10.779378 | 0.951862 | 72.699997 | 0.921871 | 0.331899 | 0.356554 | 0.790050 | 0.209637 |
| 75 | Australia | 2016 | 7.250080 | 10.791088 | 0.942334 | 73.000000 | 0.922316 | 0.238558 | 0.398545 | 0.790868 | 0.236086 |
| 76 | Australia | 2017 | 7.257038 | 10.797644 | 0.949958 | 73.300003 | 0.910550 | 0.317330 | 0.411347 | 0.780079 | 0.225361 |
| 77 | Australia | 2018 | 7.176993 | 10.811262 | 0.940137 | 73.599998 | 0.916028 | 0.146455 | 0.404647 | 0.759019 | 0.187456 |
| 78 | Australia | 2019 | 7.233995 | 10.814893 | 0.942774 | 73.900002 | 0.917537 | 0.120682 | 0.430209 | 0.770044 | 0.202190 |
| 79 | Australia | 2020 | 7.137368 | 10.759864 | 0.936517 | 74.199997 | 0.905283 | 0.210030 | 0.491095 | 0.769182 | 0.205078 |
| 80 | Austria | 2006 | 7.122211 | 10.841940 | 0.936350 | 70.760002 | 0.941382 | 0.302386 | 0.490111 | 0.823105 | 0.173812 |
| 81 | Austria | 2008 | 7.180954 | 10.886662 | 0.934593 | 71.080002 | 0.879069 | 0.291309 | 0.613625 | 0.832170 | 0.173195 |
| 82 | Austria | 2010 | 7.302679 | 10.861471 | 0.914193 | 71.400002 | 0.895980 | 0.130891 | 0.546145 | 0.814719 | 0.155793 |
| 83 | Austria | 2011 | 7.470513 | 10.886909 | 0.944157 | 71.540001 | 0.939356 | 0.131578 | 0.702721 | 0.789471 | 0.145238 |
| 84 | Austria | 2012 | 7.400689 | 10.889132 | 0.945142 | 71.680000 | 0.919704 | 0.117804 | 0.770586 | 0.822248 | 0.156675 |
| 85 | Austria | 2013 | 7.498803 | 10.883492 | 0.949809 | 71.820000 | 0.921734 | 0.168248 | 0.678937 | 0.787313 | 0.162603 |
| 86 | Austria | 2014 | 6.950000 | 10.882268 | 0.898920 | 71.959999 | 0.885027 | 0.117607 | 0.566931 | 0.779693 | 0.170150 |
| 87 | Austria | 2015 | 7.076447 | 10.881152 | 0.928110 | 72.099998 | 0.900305 | 0.098893 | 0.557480 | 0.798263 | 0.164469 |
| 88 | Austria | 2016 | 7.048072 | 10.890950 | 0.926319 | 72.400002 | 0.888514 | 0.079749 | 0.523641 | 0.755903 | 0.197424 |
| 89 | Austria | 2017 | 7.293728 | 10.908466 | 0.906218 | 72.699997 | 0.890031 | 0.133064 | 0.518304 | 0.747569 | 0.180269 |
| 90 | Austria | 2018 | 7.396002 | 10.927505 | 0.911668 | 73.000000 | 0.904112 | 0.053470 | 0.523061 | 0.752350 | 0.226059 |
| 91 | Austria | 2019 | 7.195361 | 10.939381 | 0.964489 | 73.300003 | 0.903428 | 0.059686 | 0.457089 | 0.774459 | 0.205170 |
| 92 | Austria | 2020 | 7.213489 | 10.851118 | 0.924831 | 73.599998 | 0.911910 | 0.011032 | 0.463830 | 0.769317 | 0.206500 |
| 93 | Azerbaijan | 2006 | 4.727871 | 9.170049 | 0.854415 | 61.880001 | 0.771528 | -0.234837 | 0.774117 | 0.511688 | 0.275695 |
| 94 | Azerbaijan | 2007 | 4.568160 | 9.385553 | 0.753247 | 62.259998 | 0.522046 | -0.206899 | 0.870910 | 0.520544 | 0.284357 |
| 95 | Azerbaijan | 2008 | 4.817189 | 9.465227 | 0.684267 | 62.639999 | 0.601043 | -0.029469 | 0.715125 | 0.577820 | 0.226795 |
| 96 | Azerbaijan | 2009 | 4.573725 | 9.534023 | 0.735970 | 63.020000 | 0.498138 | -0.086897 | 0.753850 | 0.543640 | 0.233942 |
| 97 | Azerbaijan | 2010 | 4.218611 | 9.568907 | 0.687001 | 63.400002 | 0.501071 | -0.123218 | 0.858347 | 0.526931 | 0.271873 |
| 98 | Azerbaijan | 2011 | 4.680470 | 9.540022 | 0.725194 | 63.639999 | 0.537484 | -0.104529 | 0.795119 | 0.535805 | 0.258117 |
| 99 | Azerbaijan | 2012 | 4.910772 | 9.548524 | 0.761873 | 63.880001 | 0.598859 | -0.139939 | 0.763155 | 0.553869 | 0.266093 |
| 100 | Azerbaijan | 2013 | 5.481178 | 9.592381 | 0.769690 | 64.120003 | 0.671957 | -0.167769 | 0.698820 | 0.618874 | 0.242455 |
| 101 | Azerbaijan | 2014 | 5.251530 | 9.607490 | 0.799433 | 64.360001 | 0.732773 | -0.208170 | 0.653845 | 0.597627 | 0.219982 |
| 102 | Azerbaijan | 2015 | 5.146775 | 9.606018 | 0.785703 | 64.599998 | 0.764289 | -0.197727 | 0.615553 | 0.606569 | 0.206114 |
| 103 | Azerbaijan | 2016 | 5.303895 | 9.563725 | 0.777271 | 64.900002 | 0.712573 | -0.204162 | 0.606771 | 0.597593 | 0.191117 |
| 104 | Azerbaijan | 2017 | 5.152279 | 9.555448 | 0.787039 | 65.199997 | 0.731030 | -0.225129 | 0.652539 | 0.592359 | 0.198319 |
| 105 | Azerbaijan | 2018 | 5.167995 | 9.561677 | 0.781230 | 65.500000 | 0.772449 | -0.231613 | 0.561206 | 0.592575 | 0.191392 |
| 106 | Azerbaijan | 2019 | 5.173389 | 9.575251 | 0.886756 | 65.800003 | 0.854249 | -0.214163 | 0.457261 | 0.642547 | 0.163920 |
| 107 | Bahrain | 2009 | 5.700523 | 10.709387 | 0.904143 | 65.940002 | 0.895931 | 0.037422 | 0.506104 | 0.763664 | 0.421889 |
| 108 | Bahrain | 2010 | 5.936869 | 10.705819 | 0.877115 | 66.300003 | 0.862003 | -0.000584 | 0.714620 | 0.684588 | 0.422671 |
| 109 | Bahrain | 2011 | 4.823976 | 10.695849 | 0.907868 | 66.580002 | 0.869870 | -0.051371 | 0.582522 | 0.543588 | 0.513719 |
| 110 | Bahrain | 2012 | 5.027187 | 10.715547 | 0.911350 | 66.860001 | 0.681823 | NaN | 0.437915 | 0.589015 | 0.380815 |
| 111 | Bahrain | 2013 | 6.689711 | 10.756761 | 0.883781 | 67.139999 | 0.809206 | NaN | 0.524703 | 0.768383 | 0.306209 |
| 112 | Bahrain | 2014 | 6.165134 | 10.783467 | NaN | 67.419998 | NaN | NaN | NaN | NaN | NaN |
| 113 | Bahrain | 2015 | 6.007375 | 10.785271 | 0.852551 | 67.699997 | 0.849521 | 0.112021 | NaN | 0.715543 | 0.302972 |
| 114 | Bahrain | 2016 | 6.169673 | 10.780850 | 0.862700 | 68.099998 | 0.888691 | 0.088187 | NaN | 0.787187 | 0.283466 |
| 115 | Bahrain | 2017 | 6.227321 | 10.771480 | 0.875747 | 68.500000 | 0.905859 | 0.136318 | NaN | 0.813571 | 0.289760 |
| 116 | Bahrain | 2019 | 7.098012 | 10.714991 | 0.877929 | 69.300003 | 0.906536 | 0.047863 | NaN | 0.761623 | 0.317106 |
| 117 | Bahrain | 2020 | 6.173176 | 10.619904 | 0.847745 | 69.699997 | 0.945233 | 0.132441 | NaN | 0.789795 | 0.296835 |
| 118 | Bangladesh | 2006 | 4.318909 | 7.782841 | 0.672002 | 59.020000 | 0.611664 | 0.068273 | 0.785916 | 0.599945 | 0.320793 |
| 119 | Bangladesh | 2007 | 4.607322 | 7.838781 | 0.514171 | 59.439999 | 0.604538 | 0.040335 | 0.806117 | 0.634599 | 0.313138 |
| 120 | Bangladesh | 2008 | 5.052279 | 7.885724 | 0.466553 | 59.860001 | 0.606012 | -0.043634 | 0.801820 | 0.725387 | 0.231861 |
| 121 | Bangladesh | 2009 | 5.082851 | 7.923776 | 0.527814 | 60.279999 | 0.630931 | -0.074515 | 0.776004 | 0.670300 | 0.223254 |
| 122 | Bangladesh | 2010 | 4.858481 | 7.966749 | 0.549398 | 60.700001 | 0.659006 | -0.016196 | 0.773530 | 0.628580 | 0.292425 |
| 123 | Bangladesh | 2011 | 4.985649 | 8.017946 | 0.606459 | 61.119999 | 0.837995 | -0.069335 | 0.757003 | 0.684994 | 0.234982 |
| 124 | Bangladesh | 2012 | 4.724444 | 8.069572 | 0.581765 | 61.540001 | 0.667682 | -0.034349 | 0.764894 | 0.713508 | 0.183245 |
| 125 | Bangladesh | 2013 | 4.660161 | 8.116403 | 0.530140 | 61.959999 | 0.741518 | -0.015539 | 0.742774 | 0.619046 | 0.246053 |
| 126 | Bangladesh | 2014 | 4.635565 | 8.163822 | 0.577065 | 62.380001 | 0.735513 | -0.098169 | 0.789375 | NaN | 0.230678 |
| 127 | Bangladesh | 2015 | 4.633474 | 8.216118 | 0.601468 | 62.799999 | 0.814796 | -0.068449 | 0.720601 | 0.634508 | 0.225754 |
| 128 | Bangladesh | 2016 | 4.556141 | 8.273924 | 0.649117 | 63.299999 | 0.874700 | -0.088731 | 0.687854 | 0.559939 | 0.235022 |
| 129 | Bangladesh | 2017 | 4.309771 | 8.333532 | 0.712553 | 63.799999 | 0.896217 | 0.011620 | 0.635014 | 0.568827 | 0.213506 |
| 130 | Bangladesh | 2018 | 4.499217 | 8.398730 | 0.705556 | 64.300003 | 0.901471 | -0.043335 | 0.701421 | 0.541345 | 0.361238 |
| 131 | Bangladesh | 2019 | 5.114217 | 8.466684 | 0.673172 | 64.800003 | 0.901937 | -0.051466 | 0.656005 | 0.537235 | 0.369472 |
| 132 | Bangladesh | 2020 | 5.279987 | 8.472195 | 0.739338 | 65.300003 | 0.777467 | -0.008851 | 0.741659 | 0.582381 | 0.331709 |
| 133 | Belarus | 2006 | 5.657650 | 9.489099 | 0.917899 | 61.099998 | 0.707080 | -0.246003 | 0.708275 | 0.605487 | 0.269400 |
| 134 | Belarus | 2007 | 5.616976 | 9.576188 | 0.857528 | 61.400002 | 0.667300 | -0.224807 | 0.694849 | 0.595992 | 0.234981 |
| 135 | Belarus | 2008 | 5.463332 | 9.676768 | 0.903700 | 61.700001 | 0.639924 | -0.220034 | 0.696496 | NaN | 0.245659 |
| 136 | Belarus | 2009 | 5.564131 | 9.680996 | 0.907778 | 62.000000 | 0.679293 | -0.202994 | 0.675543 | 0.565597 | 0.223292 |
| 137 | Belarus | 2010 | 5.525923 | 9.757792 | 0.918000 | 62.299999 | 0.700064 | -0.162565 | 0.706121 | 0.566530 | 0.208272 |
| 138 | Belarus | 2011 | 5.225308 | 9.812018 | 0.909888 | 62.880001 | 0.656011 | -0.167933 | 0.671939 | 0.520890 | 0.249455 |
| 139 | Belarus | 2012 | 5.749043 | 9.829665 | 0.901962 | 63.459999 | 0.645249 | -0.217269 | 0.657430 | 0.523195 | 0.180765 |
| 140 | Belarus | 2013 | 5.876466 | 9.839491 | 0.922506 | 64.040001 | 0.723431 | -0.177454 | 0.653039 | 0.608714 | 0.206220 |
| 141 | Belarus | 2014 | 5.812401 | 9.855708 | 0.880259 | 64.620003 | 0.647185 | -0.048226 | 0.681509 | 0.618929 | 0.208536 |
| 142 | Belarus | 2015 | 5.718908 | 9.815067 | 0.924073 | 65.199997 | 0.622753 | -0.091338 | 0.668678 | 0.583727 | 0.184310 |
| 143 | Belarus | 2016 | 5.177899 | 9.788223 | 0.926551 | 65.500000 | 0.658229 | -0.125487 | 0.664055 | 0.553870 | 0.182106 |
| 144 | Belarus | 2017 | 5.552915 | 9.813574 | 0.900256 | 65.800003 | 0.620979 | -0.121549 | 0.654113 | 0.540906 | 0.232768 |
| 145 | Belarus | 2018 | 5.233770 | 9.846136 | 0.904569 | 66.099998 | 0.643602 | -0.174485 | 0.718455 | 0.450333 | 0.235729 |
| 146 | Belarus | 2019 | 5.821453 | 9.860039 | 0.916740 | 66.400002 | 0.656934 | -0.185933 | 0.545905 | 0.590851 | 0.189821 |
| 147 | Belgium | 2005 | 7.262290 | 10.744605 | 0.934875 | 69.900002 | 0.923843 | NaN | 0.597554 | 0.796279 | 0.260380 |
| 148 | Belgium | 2007 | 7.218840 | 10.791979 | 0.921603 | 70.260002 | 0.900870 | 0.069500 | 0.721093 | 0.813477 | 0.217604 |
| 149 | Belgium | 2008 | 7.116591 | 10.788538 | 0.922977 | 70.440002 | 0.887027 | 0.006973 | 0.651801 | 0.813123 | 0.241798 |
| 150 | Belgium | 2010 | 6.853514 | 10.779181 | 0.930570 | 70.800003 | 0.806930 | 0.022295 | 0.697366 | 0.828259 | 0.240364 |
| 151 | Belgium | 2011 | 7.111364 | 10.782974 | 0.936955 | 70.919998 | 0.880154 | -0.014154 | 0.711044 | 0.834545 | 0.225056 |
| 152 | Belgium | 2012 | 6.935122 | 10.784138 | 0.927117 | 71.040001 | 0.855267 | -0.050071 | 0.757573 | 0.820486 | 0.238277 |
| 153 | Belgium | 2013 | 7.103661 | 10.784006 | 0.909186 | 71.160004 | 0.890711 | 0.016690 | 0.573664 | 0.797417 | 0.217139 |
| 154 | Belgium | 2014 | 6.855329 | 10.795229 | 0.943549 | 71.279999 | 0.860954 | 0.001345 | 0.511976 | 0.797634 | 0.251557 |
| 155 | Belgium | 2015 | 6.904219 | 10.809559 | 0.885209 | 71.400002 | 0.869475 | 0.062215 | 0.468785 | 0.805178 | 0.239959 |
| 156 | Belgium | 2016 | 6.948936 | 10.819170 | 0.928964 | 71.599998 | 0.865759 | -0.055826 | 0.496659 | 0.764590 | 0.259653 |
| 157 | Belgium | 2017 | 6.928348 | 10.834178 | 0.921639 | 71.800003 | 0.856802 | 0.054314 | 0.543046 | 0.786368 | 0.233598 |
| 158 | Belgium | 2018 | 6.892172 | 10.844393 | 0.929816 | 72.000000 | 0.808387 | -0.124600 | 0.630412 | 0.749563 | 0.250297 |
| 159 | Belgium | 2019 | 6.772138 | 10.853364 | 0.884230 | 72.199997 | 0.776204 | -0.171521 | 0.672498 | 0.733456 | 0.243631 |
| 160 | Belgium | 2020 | 6.838761 | 10.770537 | 0.903559 | 72.400002 | 0.766918 | -0.163784 | 0.633627 | 0.646510 | 0.260189 |
| 161 | Belize | 2007 | 6.450644 | 8.892479 | 0.872267 | 61.599998 | 0.705306 | 0.032754 | 0.768984 | 0.758783 | 0.250596 |
| 162 | Belize | 2014 | 5.955647 | 8.883127 | 0.756932 | 62.220001 | 0.873569 | 0.021996 | 0.782105 | 0.754977 | 0.281604 |
| 163 | Benin | 2006 | 3.329802 | 7.865885 | 0.444781 | 50.099998 | 0.580069 | -0.011183 | 0.789862 | 0.587210 | 0.309100 |
| 164 | Benin | 2008 | 3.667140 | 7.915053 | 0.382374 | 50.900002 | 0.709477 | -0.004316 | 0.825246 | 0.583623 | 0.302546 |
| 165 | Benin | 2011 | 3.870280 | 7.903917 | 0.477494 | 51.980000 | 0.772919 | -0.142235 | 0.849472 | 0.625820 | 0.218678 |
| 166 | Benin | 2012 | 3.193469 | 7.922932 | 0.523027 | 52.259998 | 0.768971 | -0.111311 | 0.805978 | 0.582524 | 0.230665 |
| 167 | Benin | 2013 | 3.479413 | 7.964470 | 0.576823 | 52.540001 | 0.783240 | -0.084775 | 0.855956 | 0.702019 | 0.216339 |
| 168 | Benin | 2014 | 3.347419 | 7.998286 | 0.506091 | 52.820000 | 0.775546 | -0.095703 | 0.854827 | 0.589645 | 0.273385 |
| 169 | Benin | 2015 | 3.624664 | 7.988194 | 0.434389 | 53.099998 | 0.733384 | -0.026638 | 0.850098 | 0.592222 | 0.373397 |
| 170 | Benin | 2016 | 4.007358 | 7.993432 | 0.492816 | 53.500000 | 0.779795 | -0.065072 | 0.837716 | 0.608237 | 0.455768 |
| 171 | Benin | 2017 | 4.853181 | 8.021096 | 0.435879 | 53.900002 | 0.726808 | -0.064986 | 0.767235 | 0.614722 | 0.457920 |
| 172 | Benin | 2018 | 5.819827 | 8.058573 | 0.503544 | 54.299999 | 0.713264 | 0.002149 | 0.746511 | 0.646655 | 0.467872 |
| 173 | Benin | 2019 | 4.976361 | 8.097825 | 0.442154 | 54.700001 | 0.770360 | -0.016129 | 0.698347 | 0.658774 | 0.441399 |
| 174 | Benin | 2020 | 4.407746 | 8.102292 | 0.506636 | 55.099998 | 0.783115 | -0.083489 | 0.531884 | 0.608585 | 0.304512 |
| 175 | Bhutan | 2013 | 5.569092 | 9.122986 | 0.818949 | 59.599998 | 0.810201 | 0.352631 | 0.802428 | 0.778723 | 0.217350 |
| 176 | Bhutan | 2014 | 4.938578 | 9.166805 | 0.880342 | 59.900002 | 0.834222 | 0.267873 | 0.650338 | 0.858864 | 0.324098 |
| 177 | Bhutan | 2015 | 5.082129 | 9.218924 | 0.847574 | 60.200001 | 0.830102 | 0.277412 | 0.633956 | 0.809641 | 0.311589 |
| 178 | Bolivia | 2006 | 5.373986 | 8.686212 | 0.834280 | 59.000000 | 0.770135 | -0.044180 | 0.794484 | 0.739243 | 0.431945 |
| 179 | Bolivia | 2007 | 5.628419 | 8.713645 | 0.796136 | 59.500000 | 0.779935 | 0.000676 | 0.816994 | 0.771075 | 0.387786 |
| 180 | Bolivia | 2008 | 5.297873 | 8.756404 | 0.785262 | 60.000000 | 0.725620 | -0.091705 | 0.801420 | 0.780654 | 0.392080 |
| 181 | Bolivia | 2009 | 6.085579 | 8.772761 | 0.831320 | 60.500000 | 0.778939 | -0.036097 | 0.762605 | 0.796764 | 0.372369 |
| 182 | Bolivia | 2010 | 5.780620 | 8.796763 | 0.807186 | 61.000000 | 0.703341 | -0.068468 | 0.781343 | 0.766100 | 0.349597 |
| 183 | Bolivia | 2011 | 5.778874 | 8.831271 | 0.816783 | 61.340000 | 0.781674 | -0.039204 | 0.824854 | 0.760786 | 0.361486 |
| 184 | Bolivia | 2012 | 6.018895 | 8.865225 | 0.780819 | 61.680000 | 0.862380 | -0.014860 | 0.839701 | 0.782481 | 0.408880 |
| 185 | Bolivia | 2013 | 5.767429 | 8.915230 | 0.802738 | 62.020000 | 0.845932 | -0.066837 | 0.811857 | 0.759099 | 0.410302 |
| 186 | Bolivia | 2014 | 5.864799 | 8.952947 | 0.821345 | 62.360001 | 0.881059 | 0.017844 | 0.831854 | 0.808609 | 0.398219 |
| 187 | Bolivia | 2015 | 5.834329 | 8.985247 | 0.828706 | 62.700001 | 0.883625 | -0.029515 | 0.862374 | 0.785768 | 0.392903 |
| 188 | Bolivia | 2016 | 5.769723 | 9.012200 | 0.795959 | 63.000000 | 0.881749 | -0.046750 | 0.852593 | 0.783009 | 0.376412 |
| 189 | Bolivia | 2017 | 5.650553 | 9.038804 | 0.778662 | 63.299999 | 0.883905 | -0.120381 | 0.819262 | 0.698195 | 0.433944 |
| 190 | Bolivia | 2018 | 5.915734 | 9.065954 | 0.827159 | 63.599998 | 0.863247 | -0.092877 | 0.786045 | 0.741973 | 0.387469 |
| 191 | Bolivia | 2019 | 5.674271 | 9.073888 | 0.784301 | 63.900002 | 0.881311 | -0.085674 | 0.857220 | 0.751408 | 0.419328 |
| 192 | Bolivia | 2020 | 5.559259 | 8.997990 | 0.804811 | 64.199997 | 0.877032 | -0.053764 | 0.868208 | 0.789818 | 0.381791 |
| 193 | Bosnia and Herzegovina | 2007 | 4.899807 | 9.266820 | 0.765604 | 66.040001 | 0.341566 | 0.005994 | 0.926125 | 0.612804 | 0.296466 |
| 194 | Bosnia and Herzegovina | 2009 | 4.963477 | 9.296339 | 0.735232 | 66.480003 | 0.257534 | -0.025500 | 0.958740 | 0.571649 | 0.390204 |
| 195 | Bosnia and Herzegovina | 2010 | 4.668518 | 9.312170 | 0.772754 | 66.699997 | 0.364967 | -0.127803 | 0.933030 | 0.516695 | 0.409213 |
| 196 | Bosnia and Herzegovina | 2011 | 4.994671 | 9.333239 | 0.725243 | 66.739998 | 0.333312 | -0.034567 | 0.924784 | 0.596073 | 0.325735 |
| 197 | Bosnia and Herzegovina | 2012 | 4.773145 | 9.341687 | 0.778860 | 66.779999 | 0.419789 | -0.012567 | 0.953422 | 0.547963 | 0.338241 |
| 198 | Bosnia and Herzegovina | 2013 | 5.123664 | 9.382378 | 0.766828 | 66.820000 | 0.390342 | 0.041853 | 0.969836 | 0.543630 | 0.314516 |
| 199 | Bosnia and Herzegovina | 2014 | 5.248954 | 9.411018 | 0.787652 | 66.860001 | 0.411937 | 0.231839 | 0.976340 | 0.531436 | 0.262175 |
| 200 | Bosnia and Herzegovina | 2015 | 5.117178 | 9.456696 | 0.655724 | 66.900002 | 0.630698 | -0.054572 | 0.959854 | 0.533987 | 0.286234 |
| 201 | Bosnia and Herzegovina | 2016 | 5.180865 | 9.500314 | 0.807705 | 67.199997 | 0.633454 | 0.133866 | 0.957312 | 0.640764 | 0.304080 |
| 202 | Bosnia and Herzegovina | 2017 | 5.089902 | 9.531589 | 0.775295 | 67.500000 | 0.563799 | 0.091783 | 0.923343 | 0.597342 | 0.270746 |
| 203 | Bosnia and Herzegovina | 2018 | 5.887401 | 9.576346 | 0.835890 | 67.800003 | 0.658846 | 0.123263 | 0.912858 | 0.642940 | 0.277365 |
| 204 | Bosnia and Herzegovina | 2019 | 6.015522 | 9.608767 | 0.873142 | 68.099998 | 0.721563 | 0.079362 | 0.962908 | 0.632990 | 0.238069 |
| 205 | Bosnia and Herzegovina | 2020 | 5.515816 | 9.583344 | 0.898519 | 68.400002 | 0.740251 | 0.137954 | 0.916052 | 0.644237 | 0.325412 |
| 206 | Botswana | 2006 | 4.739367 | 9.492278 | 0.883036 | 46.820000 | 0.823775 | -0.194722 | 0.723239 | 0.688109 | 0.225759 |
| 207 | Botswana | 2008 | 5.451147 | 9.589868 | 0.831905 | 49.860001 | 0.857776 | -0.164389 | 0.806226 | 0.731180 | 0.217886 |
| 208 | Botswana | 2010 | 3.553020 | 9.555798 | 0.865625 | 52.900002 | 0.826219 | -0.142860 | 0.813985 | 0.690273 | 0.172184 |
| 209 | Botswana | 2011 | 3.519921 | 9.600382 | 0.860028 | 53.680000 | 0.812514 | -0.250003 | 0.816158 | 0.739315 | 0.159783 |
| 210 | Botswana | 2012 | 4.835939 | 9.632069 | 0.836743 | 54.459999 | 0.799410 | -0.202824 | 0.814423 | 0.773364 | 0.171257 |
| 211 | Botswana | 2013 | 4.128299 | 9.728311 | 0.855571 | 55.240002 | 0.767357 | -0.154177 | 0.748848 | 0.697809 | 0.243771 |
| 212 | Botswana | 2014 | 4.031197 | 9.756402 | 0.859478 | 56.020000 | 0.791371 | -0.104892 | 0.743074 | 0.674190 | 0.245051 |
| 213 | Botswana | 2015 | 3.761965 | 9.724023 | 0.815656 | 56.799999 | 0.857169 | -0.116254 | 0.860293 | 0.746204 | 0.261428 |
| 214 | Botswana | 2016 | 3.498937 | 9.747831 | 0.768303 | 57.500000 | 0.851695 | -0.252724 | 0.729172 | 0.685667 | 0.251837 |
| 215 | Botswana | 2017 | 3.504881 | 9.755754 | 0.768259 | 58.200001 | 0.817308 | -0.247892 | 0.731441 | 0.656396 | 0.276253 |
| 216 | Botswana | 2018 | 3.461366 | 9.777593 | 0.794936 | 58.900002 | 0.817621 | -0.254148 | 0.806945 | 0.729643 | 0.267084 |
| 217 | Botswana | 2019 | 3.471085 | 9.785069 | 0.773667 | 59.599998 | 0.832543 | -0.239001 | 0.792080 | 0.711796 | 0.272722 |
| 218 | Brazil | 2005 | 6.636771 | 9.438417 | 0.882923 | 63.299999 | 0.882186 | NaN | 0.744994 | 0.818337 | 0.301780 |
| 219 | Brazil | 2007 | 6.320673 | 9.514919 | 0.886402 | 63.779999 | 0.776645 | -0.016235 | 0.728038 | 0.858976 | 0.299223 |
| 220 | Brazil | 2008 | 6.691425 | 9.554664 | 0.878108 | 64.019997 | 0.781931 | -0.077661 | 0.688273 | 0.820272 | 0.265486 |
| 221 | Brazil | 2009 | 7.000832 | 9.543785 | 0.912818 | 64.260002 | 0.766716 | -0.055252 | 0.722515 | 0.832505 | 0.274103 |
| 222 | Brazil | 2010 | 6.837331 | 9.606989 | 0.905528 | 64.500000 | 0.805949 | -0.053969 | 0.656036 | 0.816655 | 0.249881 |
| 223 | Brazil | 2011 | 7.037817 | 9.636804 | 0.916253 | 64.760002 | 0.833656 | -0.072337 | 0.662167 | 0.807467 | 0.267524 |
| 224 | Brazil | 2012 | 6.660004 | 9.646898 | 0.890314 | 65.019997 | 0.848606 | NaN | 0.622543 | 0.754625 | 0.349759 |
| 225 | Brazil | 2013 | 7.140283 | 9.667768 | 0.910422 | 65.279999 | 0.784815 | -0.094682 | 0.706954 | 0.817662 | 0.275668 |
| 226 | Brazil | 2014 | 6.980999 | 9.664237 | 0.898316 | 65.540001 | 0.713814 | -0.115171 | 0.710303 | 0.788230 | 0.273541 |
| 227 | Brazil | 2015 | 6.546897 | 9.619746 | 0.906693 | 65.800003 | 0.798935 | -0.015562 | 0.771339 | 0.755194 | 0.324699 |
| 228 | Brazil | 2016 | 6.374817 | 9.578201 | 0.912455 | 66.000000 | 0.806572 | -0.100316 | 0.781093 | 0.763112 | 0.302084 |
| 229 | Brazil | 2017 | 6.332929 | 9.583272 | 0.904694 | 66.199997 | 0.764793 | -0.175128 | 0.794457 | 0.715945 | 0.307717 |
| 230 | Brazil | 2018 | 6.190922 | 9.588520 | 0.881505 | 66.400002 | 0.750609 | -0.117002 | 0.763251 | 0.749728 | 0.349656 |
| 231 | Brazil | 2019 | 6.451149 | 9.592306 | 0.899175 | 66.599998 | 0.830206 | -0.061973 | 0.761841 | 0.760846 | 0.337051 |
| 232 | Brazil | 2020 | 6.109718 | 9.522141 | 0.830832 | 66.800003 | 0.786235 | -0.052820 | 0.728772 | 0.692024 | 0.389139 |
| 233 | Bulgaria | 2007 | 3.843798 | 9.715486 | 0.831508 | 65.099998 | 0.565787 | -0.137790 | 0.976061 | 0.594433 | 0.226256 |
| 234 | Bulgaria | 2010 | 3.912276 | 9.765453 | 0.843272 | 65.699997 | 0.544536 | -0.144253 | 0.940970 | 0.545824 | 0.237594 |
| 235 | Bulgaria | 2011 | 3.875382 | 9.795103 | 0.860272 | 65.800003 | 0.663528 | -0.227830 | 0.947979 | 0.533738 | 0.270931 |
| 236 | Bulgaria | 2012 | 4.222297 | 9.804495 | 0.837967 | 65.900002 | 0.641256 | -0.171941 | 0.938209 | 0.573091 | 0.236633 |
| 237 | Bulgaria | 2013 | 3.993021 | 9.813273 | 0.829132 | 66.000000 | 0.603213 | -0.190944 | 0.962047 | 0.622750 | 0.278313 |
| 238 | Bulgaria | 2014 | 4.438440 | 9.837726 | 0.885949 | 66.099998 | 0.575596 | -0.054812 | 0.954637 | 0.627810 | 0.235594 |
| 239 | Bulgaria | 2015 | 4.865401 | 9.883226 | 0.907517 | 66.199997 | 0.636818 | -0.199828 | 0.941280 | 0.642794 | 0.214224 |
| 240 | Bulgaria | 2016 | 4.837561 | 9.927648 | 0.926036 | 66.400002 | 0.700266 | -0.170193 | 0.935988 | 0.621855 | 0.171700 |
| 241 | Bulgaria | 2017 | 5.096902 | 9.969418 | 0.941755 | 66.599998 | 0.689047 | -0.154141 | 0.910800 | 0.614217 | 0.188637 |
| 242 | Bulgaria | 2018 | 5.098814 | 10.007013 | 0.923853 | 66.800003 | 0.724336 | -0.176177 | 0.952014 | 0.639022 | 0.189091 |
| 243 | Bulgaria | 2019 | 5.108438 | 10.047213 | 0.948204 | 67.000000 | 0.821930 | -0.108587 | 0.942806 | 0.662825 | 0.199888 |
| 244 | Bulgaria | 2020 | 5.597723 | 9.990658 | 0.916242 | 67.199997 | 0.818225 | -0.004322 | 0.900633 | 0.705835 | 0.221351 |
| 245 | Burkina Faso | 2006 | 3.801491 | 7.366805 | 0.796405 | 46.660000 | 0.588338 | 0.028233 | 0.797701 | 0.716253 | 0.265572 |
| 246 | Burkina Faso | 2007 | 4.017130 | 7.376977 | 0.770785 | 47.419998 | 0.582292 | -0.060116 | 0.832765 | 0.650698 | 0.280695 |
| 247 | Burkina Faso | 2008 | 3.846439 | 7.403108 | 0.726651 | 48.180000 | 0.612064 | -0.100825 | 0.887124 | 0.523474 | 0.303892 |
| 248 | Burkina Faso | 2010 | 4.035561 | 7.452925 | 0.773104 | 49.700001 | 0.586581 | -0.036145 | 0.767335 | 0.590039 | 0.216673 |
| 249 | Burkina Faso | 2011 | 4.785367 | 7.486960 | 0.709528 | 50.240002 | 0.724568 | -0.104568 | 0.706798 | 0.578625 | 0.204736 |
| 250 | Burkina Faso | 2012 | 3.955008 | 7.519517 | 0.743766 | 50.779999 | 0.621849 | -0.069597 | 0.726287 | 0.544851 | 0.299723 |
| 251 | Burkina Faso | 2013 | 3.325950 | 7.546011 | 0.745217 | 51.320000 | 0.741257 | -0.015849 | 0.764721 | 0.629771 | 0.286766 |
| 252 | Burkina Faso | 2014 | 3.481348 | 7.558751 | 0.742262 | 51.860001 | 0.709965 | -0.003699 | 0.800758 | 0.613732 | 0.255644 |
| 253 | Burkina Faso | 2015 | 4.418930 | 7.567736 | 0.705393 | 52.400002 | 0.659103 | 0.003571 | 0.692724 | 0.579356 | 0.359288 |
| 254 | Burkina Faso | 2016 | 4.205635 | 7.596462 | 0.764401 | 52.900002 | 0.644682 | -0.000543 | 0.720542 | 0.616067 | 0.337300 |
| 255 | Burkina Faso | 2017 | 4.646891 | 7.627303 | 0.784761 | 53.400002 | 0.613775 | -0.063232 | 0.727451 | 0.585172 | 0.353821 |
| 256 | Burkina Faso | 2018 | 4.927236 | 7.664604 | 0.664859 | 53.900002 | 0.720743 | -0.013175 | 0.757399 | 0.710884 | 0.342866 |
| 257 | Burkina Faso | 2019 | 4.740893 | 7.691488 | 0.683102 | 54.400002 | 0.677547 | -0.004090 | 0.729397 | 0.690926 | 0.364775 |
| 258 | Burundi | 2008 | 3.563228 | 6.718762 | 0.290934 | 49.020000 | 0.260069 | -0.018894 | 0.859814 | 0.439698 | 0.252771 |
| 259 | Burundi | 2009 | 3.791681 | 6.723309 | 0.325693 | 49.660000 | 0.427356 | -0.019278 | 0.718203 | 0.640622 | 0.163643 |
| 260 | Burundi | 2011 | 3.705894 | 6.748176 | 0.422240 | 50.680000 | 0.489863 | -0.062434 | 0.677108 | 0.688907 | 0.190345 |
| 261 | Burundi | 2014 | 2.904535 | 6.786983 | 0.564678 | 51.820000 | 0.431385 | -0.058800 | 0.807619 | 0.655664 | 0.251095 |
| 262 | Burundi | 2018 | 3.775283 | 6.635322 | 0.484715 | 53.400002 | 0.646399 | -0.023876 | 0.598608 | 0.666442 | 0.362767 |
| 263 | Cambodia | 2006 | 3.568745 | 7.746449 | 0.793081 | 55.299999 | NaN | 0.255207 | 0.829181 | 0.718541 | 0.341023 |
| 264 | Cambodia | 2007 | 4.155971 | 7.828794 | 0.675132 | 56.099998 | 0.818700 | 0.115517 | 0.878508 | NaN | 0.320335 |
| 265 | Cambodia | 2008 | 4.462164 | 7.878774 | 0.619264 | 56.900002 | 0.914173 | 0.045451 | 0.888392 | 0.739183 | 0.335324 |
| 266 | Cambodia | 2009 | 4.110626 | 7.864644 | 0.818258 | 57.700001 | 0.937233 | 0.152493 | 0.964779 | 0.796208 | 0.187687 |
| 267 | Cambodia | 2010 | 4.141072 | 7.907173 | 0.697164 | 58.500000 | 0.940131 | 0.349865 | 0.895714 | 0.774445 | 0.421966 |
| 268 | Cambodia | 2011 | 4.161225 | 7.959593 | 0.715519 | 58.880001 | 0.927462 | 0.418499 | 0.775356 | 0.799231 | 0.307869 |
| 269 | Cambodia | 2012 | 3.898707 | 8.013871 | 0.605529 | 59.259998 | 0.955596 | 0.246725 | 0.890136 | 0.820461 | 0.351859 |
| 270 | Cambodia | 2013 | 3.674467 | 8.068359 | 0.650590 | 59.639999 | 0.940593 | 0.163847 | 0.811992 | 0.791689 | 0.440312 |
| 271 | Cambodia | 2014 | 3.883306 | 8.120969 | 0.693434 | 60.020000 | 0.937545 | 0.239398 | 0.842555 | 0.783240 | 0.481934 |
| 272 | Cambodia | 2015 | 4.162165 | 8.172928 | 0.728610 | 60.400002 | 0.956320 | 0.210083 | 0.825130 | 0.812530 | 0.399103 |
| 273 | Cambodia | 2016 | 4.461259 | 8.225224 | 0.745901 | 60.799999 | 0.957821 | 0.076060 | 0.840417 | 0.838552 | 0.398200 |
| 274 | Cambodia | 2017 | 4.585842 | 8.275981 | 0.765095 | 61.200001 | 0.963775 | 0.087969 | 0.821023 | 0.798617 | 0.408284 |
| 275 | Cambodia | 2018 | 5.121838 | 8.333111 | 0.794605 | 61.599998 | 0.958305 | 0.035572 | NaN | 0.844593 | 0.414346 |
| 276 | Cambodia | 2019 | 4.998285 | 8.386811 | 0.759175 | 62.000000 | 0.956799 | 0.013223 | 0.828444 | 0.844354 | 0.389586 |
| 277 | Cambodia | 2020 | 4.376985 | 8.361936 | 0.724423 | 62.400002 | 0.963075 | 0.052430 | 0.863054 | 0.877954 | 0.389852 |
| 278 | Cameroon | 2006 | 3.851072 | 8.007079 | 0.689601 | 45.980000 | 0.653423 | -0.009350 | 0.907068 | 0.605588 | 0.270874 |
| 279 | Cameroon | 2007 | 4.349939 | 8.027517 | 0.717394 | 46.560001 | 0.643884 | -0.031391 | 0.910350 | 0.634789 | 0.248631 |
| 280 | Cameroon | 2008 | 4.291800 | 8.034303 | 0.696716 | 47.139999 | 0.580257 | -0.068993 | 0.945003 | 0.600211 | 0.312485 |
| 281 | Cameroon | 2009 | 4.741408 | 8.028528 | 0.728694 | 47.720001 | 0.698030 | -0.016778 | 0.925447 | 0.593139 | 0.249822 |
| 282 | Cameroon | 2010 | 4.554257 | 8.034702 | 0.758641 | 48.299999 | 0.792220 | 0.002303 | 0.874719 | 0.606357 | 0.273786 |
| 283 | Cameroon | 2011 | 4.433885 | 8.047761 | 0.737993 | 48.700001 | 0.816694 | -0.028886 | 0.869616 | 0.597826 | 0.271676 |
| 284 | Cameroon | 2012 | 4.244634 | 8.064879 | 0.742837 | 49.099998 | 0.766064 | -0.032058 | 0.898029 | 0.617999 | 0.284448 |
| 285 | Cameroon | 2013 | 4.271038 | 8.090330 | 0.760194 | 49.500000 | 0.794076 | -0.030284 | 0.867257 | 0.681132 | 0.268199 |
| 286 | Cameroon | 2014 | 4.240441 | 8.120489 | 0.777777 | 49.900002 | 0.794646 | -0.071320 | 0.855850 | 0.622733 | 0.216040 |
| 287 | Cameroon | 2015 | 5.037965 | 8.148646 | 0.646312 | 50.299999 | 0.791429 | 0.049315 | 0.868049 | 0.650875 | 0.346430 |
| 288 | Cameroon | 2016 | 4.816232 | 8.167479 | 0.659300 | 51.099998 | 0.712507 | -0.003486 | 0.879451 | 0.661523 | 0.367093 |
| 289 | Cameroon | 2017 | 5.074051 | 8.175977 | 0.694596 | 51.900002 | 0.766945 | -0.028414 | 0.843586 | 0.632339 | 0.377499 |
| 290 | Cameroon | 2018 | 5.250738 | 8.189674 | 0.676825 | 52.700001 | 0.816305 | 0.035603 | 0.884442 | 0.642437 | 0.355642 |
| 291 | Cameroon | 2019 | 4.936738 | 8.203218 | 0.710965 | 53.500000 | 0.711500 | -0.007858 | 0.817170 | 0.629451 | 0.326395 |
| 292 | Cameroon | 2020 | 5.241078 | 8.174634 | 0.720047 | 54.299999 | 0.674509 | 0.049266 | 0.836517 | 0.629615 | 0.386479 |
| 293 | Canada | 2005 | 7.418048 | 10.651751 | 0.961552 | 71.300003 | 0.957306 | 0.256230 | 0.502681 | 0.838544 | 0.233278 |
| 294 | Canada | 2007 | 7.481753 | 10.739180 | NaN | 71.660004 | 0.930341 | 0.249479 | 0.405608 | 0.871604 | 0.256810 |
| 295 | Canada | 2008 | 7.485604 | 10.738377 | 0.938707 | 71.839996 | 0.926315 | 0.261585 | 0.369588 | 0.890220 | 0.202175 |
| 296 | Canada | 2009 | 7.487824 | 10.697238 | 0.942845 | 72.019997 | 0.915058 | 0.246217 | 0.412622 | 0.867433 | 0.247633 |
| 297 | Canada | 2010 | 7.650346 | 10.716547 | 0.953765 | 72.199997 | 0.933949 | 0.230451 | 0.412660 | 0.878868 | 0.233113 |
| 298 | Canada | 2011 | 7.426054 | 10.737743 | 0.921669 | 72.360001 | 0.950925 | 0.253151 | 0.432992 | 0.881385 | 0.247729 |
| 299 | Canada | 2012 | 7.415144 | 10.744354 | 0.948128 | 72.519997 | 0.917961 | 0.290013 | 0.465602 | 0.856704 | 0.229332 |
| 300 | Canada | 2013 | 7.593794 | 10.756812 | 0.936239 | 72.680000 | 0.916014 | 0.315646 | 0.406236 | 0.851297 | 0.262850 |
| 301 | Canada | 2014 | 7.304258 | 10.775055 | 0.917836 | 72.839996 | 0.938898 | 0.269858 | 0.441735 | 0.833404 | 0.258602 |
| 302 | Canada | 2015 | 7.412773 | 10.774161 | 0.939067 | 73.000000 | 0.931469 | 0.252821 | 0.427152 | 0.845328 | 0.286280 |
| 303 | Canada | 2016 | 7.244846 | 10.772802 | 0.924393 | 73.199997 | 0.912424 | 0.211162 | 0.385090 | 0.824586 | 0.237423 |
| 304 | Canada | 2017 | 7.414868 | 10.792074 | 0.933749 | 73.400002 | 0.945145 | 0.162910 | 0.362034 | 0.862773 | 0.217981 |
| 305 | Canada | 2018 | 7.175497 | 10.798032 | 0.922719 | 73.599998 | 0.945783 | 0.106098 | 0.371741 | 0.823669 | 0.259398 |
| 306 | Canada | 2019 | 7.109076 | 10.800216 | 0.925304 | 73.800003 | 0.911526 | 0.111591 | 0.436434 | 0.822443 | 0.284834 |
| 307 | Canada | 2020 | 7.024905 | 10.729514 | 0.930611 | 74.000000 | 0.886892 | 0.049637 | 0.434012 | 0.795949 | 0.306674 |
| 308 | Central African Republic | 2007 | 4.160130 | 6.987199 | 0.532297 | 40.900002 | 0.662871 | 0.081043 | 0.782131 | 0.567980 | 0.329995 |
| 309 | Central African Republic | 2010 | 3.567893 | 7.091202 | 0.483334 | 42.700001 | 0.689951 | -0.035954 | 0.845377 | 0.523006 | 0.256705 |
| 310 | Central African Republic | 2011 | 3.677826 | 7.125054 | 0.387391 | 43.080002 | 0.780018 | -0.015844 | 0.834499 | 0.524068 | 0.277180 |
| 311 | Central African Republic | 2016 | 2.693061 | 6.785016 | 0.290184 | 44.900002 | 0.624057 | 0.032623 | 0.859073 | 0.578654 | 0.494268 |
| 312 | Central African Republic | 2017 | 3.475862 | 6.816519 | 0.319589 | 45.200001 | 0.645252 | 0.072786 | 0.889566 | 0.613865 | 0.599335 |
| 313 | Chad | 2006 | 3.434801 | 7.360411 | 0.724308 | 43.180000 | 0.306132 | 0.027806 | 0.961074 | 0.580500 | 0.262727 |
| 314 | Chad | 2007 | 4.141327 | 7.358672 | 0.478951 | 43.660000 | 0.294612 | -0.011461 | 0.873610 | 0.613522 | 0.245208 |
| 315 | Chad | 2008 | 4.632468 | 7.355508 | 0.570835 | 44.139999 | 0.526610 | 0.062640 | 0.943554 | 0.569130 | 0.225484 |
| 316 | Chad | 2009 | 3.639445 | 7.363704 | 0.645714 | 44.619999 | 0.401370 | 0.021430 | 0.931181 | 0.556809 | 0.221047 |
| 317 | Chad | 2010 | 3.742871 | 7.457431 | 0.733714 | 45.099998 | 0.504613 | 0.024908 | 0.857664 | 0.544883 | 0.287241 |
| 318 | Chad | 2011 | 4.393482 | 7.424624 | 0.818844 | 45.419998 | 0.540268 | 0.030600 | 0.876384 | 0.591423 | 0.289146 |
| 319 | Chad | 2012 | 4.032975 | 7.476016 | 0.672866 | 45.740002 | 0.562908 | -0.034040 | 0.884476 | 0.526546 | 0.315747 |
| 320 | Chad | 2013 | 3.507663 | 7.497941 | 0.714145 | 46.060001 | 0.488210 | -0.045458 | 0.881972 | 0.461591 | 0.314174 |
| 321 | Chad | 2014 | 3.460183 | 7.531695 | 0.733067 | 46.380001 | 0.566795 | -0.069863 | 0.880934 | 0.536371 | 0.328529 |
| 322 | Chad | 2015 | 4.322675 | 7.526775 | 0.751252 | 46.700001 | 0.474361 | -0.028660 | 0.888639 | 0.606683 | 0.358438 |
| 323 | Chad | 2016 | 4.029350 | 7.430738 | 0.616205 | 47.200001 | 0.525222 | 0.052052 | 0.819789 | 0.582458 | 0.467567 |
| 324 | Chad | 2017 | 4.558937 | 7.369620 | 0.660616 | 47.700001 | 0.614850 | 0.007875 | 0.792390 | 0.627503 | 0.538245 |
| 325 | Chad | 2018 | 4.486325 | 7.362847 | 0.577254 | 48.200001 | 0.650355 | 0.024237 | 0.762879 | 0.552737 | 0.543836 |
| 326 | Chad | 2019 | 4.250799 | 7.364944 | 0.640452 | 48.700001 | 0.537246 | 0.055001 | 0.832283 | 0.587211 | 0.460061 |
| 327 | Chile | 2006 | 6.062852 | 9.849908 | 0.835544 | 68.660004 | 0.744292 | 0.168375 | 0.633630 | 0.804136 | 0.347657 |
| 328 | Chile | 2007 | 5.697930 | 9.887110 | 0.814621 | 68.720001 | 0.661905 | 0.243907 | 0.722671 | 0.766979 | 0.342262 |
| 329 | Chile | 2008 | 5.789439 | 9.911082 | 0.803759 | 68.779999 | 0.640202 | 0.083843 | 0.740667 | 0.756524 | 0.329703 |
| 330 | Chile | 2009 | 6.493686 | 9.884724 | 0.831582 | 68.839996 | 0.746614 | 0.149212 | 0.734211 | 0.808314 | 0.299891 |
| 331 | Chile | 2010 | 6.635656 | 9.931132 | 0.856955 | 68.900002 | 0.786367 | 0.107834 | 0.701825 | 0.809173 | 0.300117 |
| 332 | Chile | 2011 | 6.526335 | 9.980473 | 0.819079 | 69.040001 | 0.700734 | 0.111660 | 0.752756 | 0.803743 | 0.316876 |
| 333 | Chile | 2012 | 6.599129 | 10.022662 | 0.855236 | 69.180000 | 0.733611 | 0.195193 | 0.782117 | 0.815391 | 0.287592 |
| 334 | Chile | 2013 | 6.740154 | 10.052527 | 0.862405 | 69.320000 | 0.736887 | 0.084833 | 0.741155 | 0.855062 | 0.285454 |
| 335 | Chile | 2014 | 6.844238 | 10.059429 | 0.861552 | 69.459999 | 0.733326 | 0.217238 | 0.758498 | 0.869811 | 0.276103 |
| 336 | Chile | 2015 | 6.532750 | 10.070428 | 0.827142 | 69.599998 | 0.768881 | 0.040594 | 0.811511 | 0.803025 | 0.332747 |
| 337 | Chile | 2016 | 6.579056 | 10.074142 | 0.841388 | 69.699997 | 0.652290 | 0.102443 | 0.858125 | 0.869229 | 0.283042 |
| 338 | Chile | 2017 | 6.320119 | 10.071705 | 0.879841 | 69.800003 | 0.790116 | -0.020043 | 0.835988 | 0.838475 | 0.291042 |
| 339 | Chile | 2018 | 6.436221 | 10.096529 | 0.890085 | 69.900002 | 0.788530 | -0.059724 | 0.816297 | 0.832562 | 0.275820 |
| 340 | Chile | 2019 | 5.942250 | 10.095188 | 0.869122 | 70.000000 | 0.659177 | -0.102766 | 0.860492 | 0.808617 | 0.337244 |
| 341 | Chile | 2020 | 6.150643 | 10.020142 | 0.888412 | 70.099998 | 0.781384 | 0.032991 | 0.811819 | 0.814603 | 0.336029 |
| 342 | China | 2006 | 4.560495 | 8.696120 | 0.747011 | 66.879997 | NaN | NaN | NaN | 0.809295 | 0.169580 |
| 343 | China | 2007 | 4.862862 | 8.823954 | 0.810852 | 67.059998 | NaN | -0.176243 | NaN | 0.817485 | 0.158614 |
| 344 | China | 2008 | 4.846295 | 8.910992 | 0.748287 | 67.239998 | 0.853072 | -0.092472 | NaN | 0.817443 | 0.146963 |
| 345 | China | 2009 | 4.454361 | 8.995857 | 0.798034 | 67.419998 | 0.771143 | -0.160481 | NaN | 0.785806 | 0.161650 |
| 346 | China | 2010 | 4.652737 | 9.092104 | 0.767753 | 67.599998 | 0.804794 | -0.133318 | NaN | 0.765265 | 0.158100 |
| 347 | China | 2011 | 5.037208 | 9.178532 | 0.787171 | 67.760002 | 0.824162 | -0.186383 | NaN | 0.820074 | 0.133503 |
| 348 | China | 2012 | 5.094917 | 9.249320 | 0.787818 | 67.919998 | 0.808255 | -0.184676 | NaN | 0.820785 | 0.158703 |
| 349 | China | 2013 | 5.241090 | 9.319200 | 0.777896 | 68.080002 | 0.804724 | -0.157777 | NaN | 0.836431 | 0.142211 |
| 350 | China | 2014 | 5.195619 | 9.385755 | 0.820366 | 68.239998 | NaN | -0.216772 | NaN | 0.853975 | 0.111518 |
| 351 | China | 2015 | 5.303878 | 9.448723 | 0.793734 | 68.400002 | NaN | -0.244435 | NaN | 0.808911 | 0.171315 |
| 352 | China | 2016 | 5.324956 | 9.509552 | 0.741703 | 68.699997 | NaN | -0.227522 | NaN | 0.826144 | 0.145625 |
| 353 | China | 2017 | 5.099061 | 9.571116 | 0.772033 | 69.000000 | 0.877618 | -0.174832 | NaN | 0.821097 | 0.214005 |
| 354 | China | 2018 | 5.131434 | 9.631892 | 0.787605 | 69.300003 | 0.895378 | -0.158510 | NaN | 0.855784 | 0.189640 |
| 355 | China | 2019 | 5.144120 | 9.687612 | 0.821936 | 69.599998 | 0.927356 | -0.173036 | NaN | 0.890780 | 0.146512 |
| 356 | China | 2020 | 5.771065 | 9.701755 | 0.808334 | 69.900002 | 0.891123 | -0.103214 | NaN | 0.789345 | 0.244918 |
| 357 | Colombia | 2006 | 6.024943 | 9.277375 | 0.910293 | 65.220001 | 0.804662 | -0.014981 | 0.807830 | 0.799651 | 0.325588 |
| 358 | Colombia | 2007 | 6.138412 | 9.330238 | 0.893707 | 65.339996 | 0.785866 | -0.040381 | 0.859761 | 0.808266 | 0.287090 |
| 359 | Colombia | 2008 | 6.168395 | 9.350784 | 0.880067 | 65.459999 | 0.795084 | -0.041800 | 0.763224 | 0.803400 | 0.307162 |
| 360 | Colombia | 2009 | 6.271605 | 9.350991 | 0.885927 | 65.580002 | 0.757101 | -0.054762 | 0.837143 | 0.842629 | 0.273131 |
| 361 | Colombia | 2010 | 6.408113 | 9.384451 | 0.892993 | 65.699997 | 0.816121 | -0.049532 | 0.814524 | 0.830626 | 0.264659 |
| 362 | Colombia | 2011 | 6.463953 | 9.441931 | 0.904147 | 65.919998 | 0.810907 | -0.073486 | 0.847269 | 0.831615 | 0.285959 |
| 363 | Colombia | 2012 | 6.374880 | 9.471291 | 0.914373 | 66.139999 | 0.827868 | -0.009422 | 0.868372 | 0.845918 | 0.293702 |
| 364 | Colombia | 2013 | 6.606551 | 9.512274 | 0.900778 | 66.360001 | 0.841173 | -0.070860 | 0.898202 | 0.850565 | 0.278114 |
| 365 | Colombia | 2014 | 6.448789 | 9.546183 | 0.907403 | 66.580002 | 0.801191 | -0.090322 | 0.886646 | 0.847080 | 0.278056 |
| 366 | Colombia | 2015 | 6.387572 | 9.563641 | 0.889900 | 66.800003 | 0.790898 | -0.100126 | 0.842899 | 0.839295 | 0.291769 |
| 367 | Colombia | 2016 | 6.233715 | 9.570699 | 0.881900 | 67.099998 | 0.834966 | -0.100342 | 0.897554 | 0.793531 | 0.294223 |
| 368 | Colombia | 2017 | 6.157342 | 9.569167 | 0.909250 | 67.400002 | 0.837555 | -0.157137 | 0.875018 | 0.836927 | 0.299309 |
| 369 | Colombia | 2018 | 5.983512 | 9.578836 | 0.870970 | 67.699997 | 0.850766 | -0.148472 | 0.854821 | 0.825455 | 0.300624 |
| 370 | Colombia | 2019 | 6.350298 | 9.597702 | 0.872579 | 68.000000 | 0.821501 | -0.172131 | 0.853646 | 0.822490 | 0.321806 |
| 371 | Colombia | 2020 | 5.709175 | 9.495491 | 0.797035 | 68.300003 | 0.840186 | -0.084642 | 0.807964 | 0.795133 | 0.340159 |
| 372 | Comoros | 2009 | 3.476027 | 7.951781 | 0.629427 | 54.360001 | 0.507845 | -0.073564 | 0.838116 | 0.671982 | 0.167317 |
| 373 | Comoros | 2010 | 3.812191 | 7.964951 | 0.721343 | 54.700001 | 0.528675 | 0.005319 | 0.741182 | 0.727508 | 0.177948 |
| 374 | Comoros | 2011 | 3.838486 | 7.980955 | 0.721833 | 55.020000 | 0.499674 | -0.074848 | 0.731508 | 0.666620 | 0.173323 |
| 375 | Comoros | 2012 | 3.955640 | 7.988264 | 0.719218 | 55.340000 | 0.534041 | -0.120782 | 0.651009 | 0.612241 | 0.211844 |
| 376 | Comoros | 2018 | 3.972820 | 8.028402 | 0.621303 | 57.200001 | 0.560182 | 0.085823 | 0.793758 | 0.747742 | 0.337494 |
| 377 | Comoros | 2019 | 4.608616 | 8.033134 | 0.632013 | 57.500000 | 0.538262 | 0.077253 | 0.762232 | 0.736222 | 0.336163 |
| 378 | Congo (Brazzaville) | 2008 | 3.819792 | 8.082047 | 0.554772 | 52.200001 | 0.525747 | -0.098091 | NaN | 0.573002 | 0.297790 |
| 379 | Congo (Brazzaville) | 2011 | 4.509824 | 8.180340 | 0.637118 | 54.580002 | 0.744807 | -0.109149 | 0.832714 | 0.621050 | 0.287876 |
| 380 | Congo (Brazzaville) | 2012 | 3.919342 | 8.191727 | 0.622330 | 54.959999 | 0.772511 | -0.111643 | 0.799654 | 0.564220 | 0.322583 |
| 381 | Congo (Brazzaville) | 2013 | 3.954951 | 8.200904 | 0.679935 | 55.340000 | 0.725816 | -0.077837 | 0.751724 | 0.609986 | 0.291402 |
| 382 | Congo (Brazzaville) | 2014 | 4.056013 | 8.242097 | 0.685935 | 55.720001 | 0.661638 | -0.110425 | 0.808413 | 0.595255 | 0.400229 |
| 383 | Congo (Brazzaville) | 2015 | 4.690830 | 8.243382 | 0.642136 | 56.099998 | 0.850172 | -0.103922 | 0.841359 | 0.606044 | 0.260671 |
| 384 | Congo (Brazzaville) | 2016 | 4.119493 | 8.189586 | 0.615449 | 56.700001 | 0.785907 | -0.071726 | 0.790386 | 0.610305 | 0.303667 |
| 385 | Congo (Brazzaville) | 2017 | 4.883991 | 8.145705 | 0.655441 | 57.299999 | 0.777783 | -0.130517 | 0.762783 | 0.598952 | 0.381641 |
| 386 | Congo (Brazzaville) | 2018 | 5.490214 | 8.135762 | 0.620623 | 57.900002 | 0.698700 | -0.092254 | 0.738020 | 0.587507 | 0.447646 |
| 387 | Congo (Brazzaville) | 2019 | 5.212623 | 8.101092 | 0.624768 | 58.500000 | 0.686452 | -0.046051 | 0.740589 | 0.645254 | 0.405041 |
| 388 | Congo (Kinshasa) | 2009 | 3.983849 | 6.728164 | 0.733060 | 49.340000 | 0.556488 | -0.022004 | 0.824010 | 0.491489 | 0.282622 |
| 389 | Congo (Kinshasa) | 2011 | 4.516964 | 6.796630 | 0.743947 | 50.340000 | 0.631109 | -0.025286 | 0.856495 | 0.616806 | 0.208352 |
| 390 | Congo (Kinshasa) | 2012 | 4.639227 | 6.831725 | 0.769546 | 50.779999 | 0.557286 | -0.034522 | 0.807407 | 0.634003 | 0.229651 |
| 391 | Congo (Kinshasa) | 2013 | 4.497477 | 6.879825 | 0.829852 | 51.220001 | 0.480394 | 0.012176 | 0.912992 | 0.589168 | 0.187095 |
| 392 | Congo (Kinshasa) | 2014 | 4.414300 | 6.937111 | 0.822286 | 51.660000 | 0.556099 | 0.009187 | 0.813676 | 0.558870 | 0.304635 |
| 393 | Congo (Kinshasa) | 2015 | 3.902742 | 6.970958 | 0.767236 | 52.099998 | 0.573764 | -0.047585 | 0.866378 | 0.589131 | 0.301049 |
| 394 | Congo (Kinshasa) | 2016 | 4.521935 | 6.961839 | 0.864155 | 52.500000 | 0.637367 | -0.024395 | 0.875000 | 0.646270 | 0.222411 |
| 395 | Congo (Kinshasa) | 2017 | 4.311033 | 6.965846 | 0.669688 | 52.900002 | 0.704240 | 0.068378 | 0.809182 | 0.550526 | 0.404262 |
| 396 | Costa Rica | 2006 | 7.082465 | 9.564669 | 0.936938 | 69.940002 | 0.882420 | 0.060331 | 0.797522 | 0.867740 | 0.235549 |
| 397 | Costa Rica | 2007 | 7.432132 | 9.629647 | 0.917678 | 69.879997 | 0.922736 | 0.097860 | 0.819655 | 0.875299 | 0.240080 |
| 398 | Costa Rica | 2008 | 6.850680 | 9.661901 | 0.915759 | 69.820000 | 0.912006 | 0.095703 | 0.815713 | 0.844217 | 0.232947 |
| 399 | Costa Rica | 2009 | 7.614929 | 9.639322 | 0.899782 | 69.760002 | 0.886061 | 0.065291 | 0.786559 | 0.876206 | 0.217024 |
| 400 | Costa Rica | 2010 | 7.271054 | 9.675203 | 0.915141 | 69.699997 | 0.881030 | 0.047454 | 0.762587 | 0.886287 | 0.221241 |
| 401 | Costa Rica | 2011 | 7.228889 | 9.705276 | 0.892048 | 69.900002 | 0.926106 | -0.033006 | 0.836583 | 0.875645 | 0.269225 |
| 402 | Costa Rica | 2012 | 7.272250 | 9.740347 | 0.902207 | 70.099998 | 0.928914 | 0.045841 | 0.794301 | 0.896885 | 0.263027 |
| 403 | Costa Rica | 2013 | 7.158000 | 9.751308 | 0.902069 | 70.300003 | 0.897879 | 0.018084 | 0.812863 | 0.850213 | 0.278147 |
| 404 | Costa Rica | 2014 | 7.247086 | 9.774683 | 0.914211 | 70.500000 | 0.926707 | 0.009626 | 0.788037 | 0.836786 | 0.289529 |
| 405 | Costa Rica | 2015 | 6.854004 | 9.799487 | 0.878273 | 70.699997 | 0.906926 | -0.059072 | 0.761419 | 0.849710 | 0.286440 |
| 406 | Costa Rica | 2016 | 7.135618 | 9.830494 | 0.900701 | 70.900002 | 0.872972 | -0.032443 | 0.780562 | 0.873584 | 0.281422 |
| 407 | Costa Rica | 2017 | 7.225182 | 9.858093 | 0.921697 | 71.099998 | 0.935618 | -0.076224 | 0.742351 | 0.874396 | 0.275440 |
| 408 | Costa Rica | 2018 | 7.141075 | 9.874401 | 0.875872 | 71.300003 | 0.941888 | -0.106974 | 0.781302 | 0.870098 | 0.325867 |
| 409 | Costa Rica | 2019 | 6.997619 | 9.885447 | 0.906077 | 71.500000 | 0.926830 | -0.145994 | 0.835628 | 0.848348 | 0.303327 |
| 410 | Croatia | 2007 | 5.820908 | 10.161589 | 0.909822 | 67.120003 | 0.662206 | -0.091904 | 0.934274 | 0.586316 | 0.337085 |
| 411 | Croatia | 2009 | 5.433320 | 10.103759 | 0.860663 | 67.639999 | 0.549258 | -0.270663 | 0.958131 | 0.636663 | 0.272170 |
| 412 | Croatia | 2010 | 5.595575 | 10.090949 | 0.796392 | 67.900002 | 0.564373 | -0.237075 | 0.972739 | 0.606828 | 0.258887 |
| 413 | Croatia | 2011 | 5.385373 | 10.091299 | 0.789739 | 68.000000 | 0.516932 | -0.197630 | 0.976777 | 0.597510 | 0.272980 |
| 414 | Croatia | 2012 | 6.027635 | 10.071725 | 0.775818 | 68.099998 | 0.541910 | -0.242314 | 0.923860 | 0.621575 | 0.271041 |
| 415 | Croatia | 2013 | 5.885463 | 10.069010 | 0.751262 | 68.199997 | 0.626700 | -0.203897 | 0.936060 | 0.589998 | 0.284730 |
| 416 | Croatia | 2014 | 5.380692 | 10.072043 | 0.645698 | 68.300003 | 0.518878 | 0.132080 | 0.917735 | 0.596179 | 0.285895 |
| 417 | Croatia | 2015 | 5.205438 | 10.104363 | 0.768363 | 68.400002 | 0.693523 | -0.096478 | 0.848546 | 0.608886 | 0.294019 |
| 418 | Croatia | 2016 | 5.416875 | 10.145592 | 0.798332 | 69.000000 | 0.671971 | -0.064612 | 0.884060 | 0.613686 | 0.336541 |
| 419 | Croatia | 2017 | 5.343166 | 10.188506 | 0.770310 | 69.599998 | 0.715822 | -0.104344 | 0.891560 | 0.655305 | 0.316488 |
| 420 | Croatia | 2018 | 5.536271 | 10.224031 | 0.909807 | 70.199997 | 0.690856 | -0.150750 | 0.925408 | 0.582044 | 0.290376 |
| 421 | Croatia | 2019 | 5.625744 | 10.257958 | 0.935989 | 70.800003 | 0.739301 | -0.137393 | 0.931615 | 0.550690 | 0.269155 |
| 422 | Croatia | 2020 | 6.507992 | 10.165817 | 0.922913 | 71.400002 | 0.836658 | -0.062968 | 0.960939 | 0.742781 | 0.285610 |
| 423 | Cuba | 2006 | 5.417869 | NaN | 0.969595 | 68.440002 | 0.281458 | NaN | NaN | 0.646712 | 0.276602 |
| 424 | Cyprus | 2006 | 6.237958 | 10.565565 | 0.878201 | 71.440002 | 0.836101 | 0.018175 | 0.712469 | 0.829413 | 0.253212 |
| 425 | Cyprus | 2009 | 6.833477 | 10.557503 | 0.811736 | 72.160004 | 0.774591 | 0.054318 | 0.801424 | 0.746213 | 0.329308 |
| 426 | Cyprus | 2010 | 6.386546 | 10.551297 | 0.822124 | 72.400002 | 0.755363 | 0.072533 | 0.833427 | 0.786111 | 0.295706 |
| 427 | Cyprus | 2011 | 6.689609 | 10.529789 | 0.843655 | 72.540001 | 0.745469 | 0.179634 | 0.840676 | 0.763074 | 0.272300 |
| 428 | Cyprus | 2012 | 6.180507 | 10.479476 | 0.767177 | 72.680000 | 0.724630 | 0.098052 | 0.870692 | 0.755317 | 0.368633 |
| 429 | Cyprus | 2013 | 5.438952 | 10.414024 | 0.744032 | 72.820000 | 0.656268 | 0.101920 | 0.867310 | 0.747812 | 0.420259 |
| 430 | Cyprus | 2014 | 5.627124 | 10.406218 | 0.770176 | 72.959999 | 0.715066 | 0.059810 | 0.868238 | 0.737284 | 0.397173 |
| 431 | Cyprus | 2015 | 5.439161 | 10.445101 | 0.769556 | 73.099998 | 0.628035 | 0.113800 | 0.892795 | 0.746730 | 0.383106 |
| 432 | Cyprus | 2016 | 5.794619 | 10.505802 | 0.786438 | 73.300003 | 0.756221 | -0.030234 | 0.897640 | 0.742049 | 0.336345 |
| 433 | Cyprus | 2017 | 6.062051 | 10.539188 | 0.818671 | 73.500000 | 0.811671 | 0.043223 | 0.851206 | 0.784188 | 0.300517 |
| 434 | Cyprus | 2018 | 6.276443 | 10.566755 | 0.825573 | 73.699997 | 0.794215 | -0.022269 | 0.848337 | 0.750122 | 0.298021 |
| 435 | Cyprus | 2019 | 6.136833 | 10.585187 | 0.776078 | 73.900002 | 0.740058 | -0.007663 | 0.865294 | 0.762677 | 0.290225 |
| 436 | Cyprus | 2020 | 6.259810 | NaN | 0.805559 | 74.099998 | 0.762782 | NaN | 0.816232 | 0.758863 | 0.283522 |
| 437 | Czech Republic | 2005 | 6.439257 | 10.324370 | 0.918759 | 67.000000 | 0.865235 | NaN | 0.900733 | 0.722875 | 0.257949 |
| 438 | Czech Republic | 2007 | 6.500194 | 10.436629 | 0.899779 | 67.440002 | 0.798949 | -0.063437 | 0.927871 | 0.736434 | 0.276907 |
| 439 | Czech Republic | 2010 | 6.249618 | 10.419456 | 0.934161 | 68.099998 | 0.779112 | -0.041806 | 0.925964 | 0.641369 | 0.244084 |
| 440 | Czech Republic | 2011 | 6.331491 | 10.435011 | 0.913511 | 68.239998 | 0.787180 | -0.106459 | 0.949788 | 0.600926 | 0.252809 |
| 441 | Czech Republic | 2012 | 6.334149 | 10.425581 | 0.912427 | 68.379997 | 0.739809 | -0.153753 | 0.956800 | 0.609041 | 0.256508 |
| 442 | Czech Republic | 2013 | 6.697656 | 10.420401 | 0.888043 | 68.519997 | 0.725946 | -0.155719 | 0.915899 | 0.719958 | 0.252653 |
| 443 | Czech Republic | 2014 | 6.483730 | 10.446137 | 0.877915 | 68.660004 | 0.800421 | -0.167946 | 0.896881 | 0.678407 | 0.235221 |
| 444 | Czech Republic | 2015 | 6.608017 | 10.495902 | 0.911363 | 68.800003 | 0.808484 | -0.145857 | 0.886467 | 0.750774 | 0.206081 |
| 445 | Czech Republic | 2016 | 6.735627 | 10.518191 | 0.930593 | 69.300003 | 0.850328 | -0.197475 | 0.900431 | 0.755702 | 0.201042 |
| 446 | Czech Republic | 2017 | 6.789568 | 10.558141 | 0.900969 | 69.800003 | 0.831786 | -0.176520 | 0.866525 | 0.738744 | 0.226650 |
| 447 | Czech Republic | 2018 | 7.034165 | 10.582860 | 0.929164 | 70.300003 | 0.790132 | -0.291852 | 0.851382 | 0.713700 | 0.178068 |
| 448 | Czech Republic | 2020 | 6.897091 | 10.530134 | 0.964054 | 71.300003 | 0.906422 | -0.127022 | 0.883700 | 0.832058 | 0.290442 |
| 449 | Denmark | 2005 | 8.018934 | 10.851397 | 0.972372 | 69.599998 | 0.971135 | NaN | 0.236522 | 0.859549 | 0.153672 |
| 450 | Denmark | 2007 | 7.834233 | 10.891111 | 0.954201 | 69.919998 | 0.932086 | 0.240024 | 0.206006 | 0.827860 | 0.194324 |
| 451 | Denmark | 2008 | 7.970892 | 10.880102 | 0.953912 | 70.080002 | 0.969788 | 0.272087 | 0.247505 | 0.756866 | 0.163091 |
| 452 | Denmark | 2009 | 7.683359 | 10.824442 | 0.938892 | 70.239998 | 0.949336 | 0.263550 | 0.205770 | 0.748949 | 0.233585 |
| 453 | Denmark | 2010 | 7.770515 | 10.838536 | 0.974977 | 70.400002 | 0.943631 | 0.242442 | 0.174896 | 0.784827 | 0.154563 |
| 454 | Denmark | 2011 | 7.788232 | 10.847698 | 0.961736 | 70.620003 | 0.934760 | 0.297531 | 0.220043 | 0.769436 | 0.174883 |
| 455 | Denmark | 2012 | 7.519909 | 10.846198 | 0.951437 | 70.839996 | 0.932628 | 0.138761 | 0.187408 | 0.773764 | 0.208570 |
| 456 | Denmark | 2013 | 7.588607 | 10.851319 | 0.964708 | 71.059998 | 0.920255 | 0.214793 | 0.170042 | 0.862347 | 0.194674 |
| 457 | Denmark | 2014 | 7.507559 | 10.862313 | 0.956344 | 71.279999 | 0.941572 | 0.118037 | 0.237218 | 0.832483 | 0.232613 |
| 458 | Denmark | 2015 | 7.514425 | 10.878405 | 0.959701 | 71.500000 | 0.941436 | 0.222084 | 0.191016 | 0.829217 | 0.217578 |
| 459 | Denmark | 2016 | 7.557783 | 10.902544 | 0.954452 | 71.800003 | 0.948231 | 0.137807 | 0.209893 | 0.836116 | 0.207583 |
| 460 | Denmark | 2017 | 7.593702 | 10.916268 | 0.952100 | 72.099998 | 0.955416 | 0.155435 | 0.181148 | 0.823667 | 0.205775 |
| 461 | Denmark | 2018 | 7.648786 | 10.934941 | 0.958219 | 72.400002 | 0.935438 | 0.018000 | 0.150607 | 0.821423 | 0.206053 |
| 462 | Denmark | 2019 | 7.693003 | 10.954033 | 0.957706 | 72.699997 | 0.963318 | 0.020324 | 0.174151 | 0.861935 | 0.181071 |
| 463 | Denmark | 2020 | 7.514631 | 10.909995 | 0.947371 | 73.000000 | 0.937932 | 0.052293 | 0.213842 | 0.817664 | 0.227102 |
| 464 | Djibouti | 2008 | 5.009330 | 8.111199 | 0.690440 | 53.259998 | 0.773457 | 0.128720 | 0.576098 | 0.754546 | 0.120192 |
| 465 | Djibouti | 2009 | 4.905925 | 7.926556 | 0.900565 | 53.779999 | 0.649316 | 0.004683 | 0.634223 | 0.662168 | 0.232133 |
| 466 | Djibouti | 2010 | 5.005811 | 7.811863 | NaN | 54.299999 | 0.763730 | -0.058336 | 0.596910 | NaN | NaN |
| 467 | Djibouti | 2011 | 4.369194 | 7.880099 | 0.632973 | 54.700001 | 0.746439 | -0.057319 | 0.518930 | 0.579303 | 0.180593 |
| 468 | Dominican Republic | 2006 | 5.087968 | 9.313571 | 0.918899 | 62.680000 | 0.858241 | 0.037693 | 0.754729 | 0.747728 | 0.274338 |
| 469 | Dominican Republic | 2007 | 5.081306 | 9.372158 | 0.847545 | 62.959999 | 0.886247 | -0.007659 | 0.771574 | 0.766554 | 0.260099 |
| 470 | Dominican Republic | 2008 | 4.842306 | 9.391065 | 0.850137 | 63.240002 | 0.848117 | -0.045099 | 0.727598 | 0.731573 | 0.329416 |
| 471 | Dominican Republic | 2009 | 5.431614 | 9.388014 | 0.878161 | 63.520000 | 0.862979 | -0.052841 | 0.805910 | 0.785393 | 0.279788 |
| 472 | Dominican Republic | 2010 | 4.735021 | 9.455829 | 0.859969 | 63.799999 | 0.823903 | -0.074849 | 0.779742 | 0.787006 | 0.281695 |
| 473 | Dominican Republic | 2011 | 5.396535 | 9.474575 | 0.872086 | 64.019997 | 0.847975 | 0.013953 | 0.788255 | 0.808841 | 0.299839 |
| 474 | Dominican Republic | 2012 | 4.753311 | 9.489464 | 0.879158 | 64.239998 | 0.840129 | -0.061735 | 0.727300 | 0.796802 | 0.297043 |
| 475 | Dominican Republic | 2013 | 5.015515 | 9.525321 | 0.878449 | 64.459999 | 0.888566 | 0.020657 | 0.751751 | 0.793314 | 0.295131 |
| 476 | Dominican Republic | 2014 | 5.387332 | 9.581879 | 0.890588 | 64.680000 | 0.904574 | -0.020420 | 0.760023 | 0.797705 | 0.300099 |
| 477 | Dominican Republic | 2015 | 5.061862 | 9.637460 | 0.893198 | 64.900002 | 0.856025 | -0.065387 | 0.755288 | 0.713908 | 0.295253 |
| 478 | Dominican Republic | 2016 | 5.238698 | 9.690702 | 0.894753 | 65.199997 | 0.872712 | -0.080135 | 0.737183 | 0.759946 | 0.278095 |
| 479 | Dominican Republic | 2017 | 5.605203 | 9.725278 | 0.894368 | 65.500000 | 0.855359 | -0.121460 | 0.760490 | 0.738944 | 0.274746 |
| 480 | Dominican Republic | 2018 | 5.433216 | 9.781984 | 0.861986 | 65.800003 | 0.866642 | -0.150292 | 0.762274 | 0.744872 | 0.291403 |
| 481 | Dominican Republic | 2019 | 6.004237 | 9.821140 | 0.884090 | 66.099998 | 0.877406 | -0.122696 | 0.745615 | 0.784218 | 0.264054 |
| 482 | Dominican Republic | 2020 | 5.168410 | 9.802446 | 0.806118 | 66.400002 | 0.834643 | -0.127834 | 0.636117 | 0.733867 | 0.313928 |
| 483 | Ecuador | 2006 | 5.024191 | 9.185779 | 0.910188 | 66.080002 | 0.671075 | -0.090794 | 0.900687 | 0.824870 | 0.356847 |
| 484 | Ecuador | 2007 | 4.995875 | 9.190714 | 0.838859 | 66.260002 | 0.669843 | -0.063085 | 0.829651 | 0.833283 | 0.286144 |
| 485 | Ecuador | 2008 | 5.296513 | 9.235755 | 0.829395 | 66.440002 | 0.640317 | -0.094336 | 0.801257 | 0.842587 | 0.283164 |
| 486 | Ecuador | 2009 | 6.021803 | 9.225117 | 0.779398 | 66.620003 | 0.736881 | -0.108082 | 0.774305 | 0.840363 | 0.255968 |
| 487 | Ecuador | 2010 | 5.838051 | 9.243869 | 0.839280 | 66.800003 | 0.723079 | -0.063229 | 0.805639 | 0.826495 | 0.220014 |
| 488 | Ecuador | 2011 | 5.795088 | 9.304221 | 0.818051 | 66.959999 | 0.788306 | -0.155053 | 0.701596 | 0.861700 | 0.270688 |
| 489 | Ecuador | 2012 | 5.960716 | 9.344117 | 0.785201 | 67.120003 | 0.825275 | -0.083768 | 0.729979 | 0.847185 | 0.333309 |
| 490 | Ecuador | 2013 | 6.019206 | 9.377429 | 0.801251 | 67.279999 | 0.786798 | -0.190550 | 0.645849 | 0.850897 | 0.266504 |
| 491 | Ecuador | 2014 | 5.945852 | 9.399179 | 0.830963 | 67.440002 | 0.719105 | -0.167210 | 0.660935 | 0.859316 | 0.305793 |
| 492 | Ecuador | 2015 | 5.964075 | 9.383989 | 0.855889 | 67.599998 | 0.800870 | -0.113920 | 0.665828 | 0.850546 | 0.322946 |
| 493 | Ecuador | 2016 | 6.115438 | 9.354581 | 0.842352 | 67.900002 | 0.846336 | -0.015232 | 0.774084 | 0.846354 | 0.365247 |
| 494 | Ecuador | 2017 | 5.839519 | 9.360303 | 0.848942 | 68.199997 | 0.879128 | -0.167036 | 0.733589 | 0.829142 | 0.314343 |
| 495 | Ecuador | 2018 | 6.128010 | 9.355457 | 0.851345 | 68.500000 | 0.869364 | -0.099171 | 0.830743 | 0.876475 | 0.328171 |
| 496 | Ecuador | 2019 | 5.809131 | 9.339202 | 0.808486 | 68.800003 | 0.829574 | -0.114833 | 0.839495 | 0.811050 | 0.373558 |
| 497 | Ecuador | 2020 | 5.354462 | 9.243865 | 0.804009 | 69.099998 | 0.828512 | -0.157090 | 0.854780 | 0.789941 | 0.416028 |
| 498 | Egypt | 2005 | 5.167754 | 9.035634 | 0.847842 | 59.700001 | 0.817362 | NaN | NaN | 0.734863 | 0.345555 |
| 499 | Egypt | 2007 | 5.540511 | 9.135076 | 0.685863 | 59.820000 | 0.609077 | -0.120520 | NaN | 0.665264 | 0.355348 |
| 500 | Egypt | 2008 | 4.631741 | 9.186407 | 0.738364 | 59.880001 | NaN | -0.087063 | 0.913642 | 0.682730 | 0.301018 |
| 501 | Egypt | 2009 | 5.066164 | 9.213439 | 0.744180 | 59.939999 | 0.611083 | -0.099577 | 0.800866 | 0.642155 | 0.339482 |
| 502 | Egypt | 2010 | 4.668916 | 9.243782 | 0.768675 | 60.000000 | 0.486279 | -0.075683 | 0.826335 | 0.566759 | 0.276346 |
| 503 | Egypt | 2011 | 4.174159 | 9.240136 | 0.753394 | 60.160000 | 0.589538 | -0.151418 | 0.858596 | 0.528634 | 0.353417 |
| 504 | Egypt | 2012 | 4.204157 | 9.240006 | 0.736645 | 60.320000 | 0.451543 | -0.137821 | 0.880383 | 0.527221 | 0.398423 |
| 505 | Egypt | 2013 | 3.558520 | 9.238947 | 0.675188 | 60.480000 | 0.473775 | -0.141244 | 0.913228 | 0.550683 | 0.483379 |
| 506 | Egypt | 2014 | 4.885073 | 9.245096 | 0.618551 | 60.639999 | 0.577938 | -0.126385 | 0.749143 | 0.542784 | 0.327350 |
| 507 | Egypt | 2015 | 4.762538 | 9.265818 | 0.729744 | 60.799999 | 0.659261 | -0.088560 | 0.684498 | 0.609594 | 0.344332 |
| 508 | Egypt | 2016 | 4.556741 | 9.286913 | 0.809219 | 61.099998 | 0.655845 | -0.141441 | 0.817527 | 0.611370 | 0.370498 |
| 509 | Egypt | 2017 | 3.929344 | 9.306967 | 0.638226 | 61.400002 | 0.592505 | -0.152355 | NaN | 0.539323 | 0.414494 |
| 510 | Egypt | 2018 | 4.005451 | 9.338411 | 0.758824 | 61.700001 | 0.681654 | -0.215410 | NaN | 0.492261 | 0.285184 |
| 511 | Egypt | 2019 | 4.327832 | 9.372736 | 0.772129 | 62.000000 | 0.773951 | -0.198710 | NaN | 0.516831 | 0.312763 |
| 512 | Egypt | 2020 | 4.472397 | 9.382727 | 0.672725 | 62.299999 | 0.769550 | -0.112342 | NaN | 0.598909 | 0.442034 |
| 513 | El Salvador | 2006 | 5.700930 | 8.873026 | 0.878409 | 62.919998 | 0.682990 | -0.055644 | 0.806596 | 0.863995 | 0.232691 |
| 514 | El Salvador | 2007 | 5.295535 | 8.887126 | 0.716827 | 63.240002 | 0.638937 | -0.014801 | 0.785099 | 0.868841 | 0.220199 |
| 515 | El Salvador | 2008 | 5.191494 | 8.908267 | 0.747411 | 63.560001 | 0.635648 | -0.078051 | 0.734727 | 0.842067 | 0.232124 |
| 516 | El Salvador | 2009 | 6.839087 | 8.882967 | 0.734113 | 63.880001 | 0.670932 | -0.103450 | 0.647528 | 0.850378 | 0.243231 |
| 517 | El Salvador | 2010 | 6.739911 | 8.899548 | 0.756654 | 64.199997 | 0.669338 | -0.063869 | 0.694180 | 0.813811 | 0.302186 |
| 518 | El Salvador | 2011 | 4.741295 | 8.932700 | 0.731278 | 64.400002 | 0.747246 | -0.126358 | 0.706553 | 0.875324 | 0.336322 |
| 519 | El Salvador | 2012 | 5.934371 | 8.956071 | 0.806015 | 64.599998 | 0.682745 | -0.154836 | 0.786295 | 0.830632 | 0.365221 |
| 520 | El Salvador | 2013 | 6.325063 | 8.973660 | 0.826859 | 64.800003 | 0.715570 | -0.149619 | 0.771751 | 0.828257 | 0.317476 |
| 521 | El Salvador | 2014 | 5.856524 | 8.986002 | 0.797612 | 65.000000 | 0.778015 | -0.194103 | 0.781460 | 0.837205 | 0.329851 |
| 522 | El Salvador | 2015 | 6.018496 | 9.004916 | 0.790755 | 65.199997 | 0.733356 | -0.156171 | 0.804544 | 0.825734 | 0.332647 |
| 523 | El Salvador | 2016 | 6.139825 | 9.025170 | 0.793660 | 65.500000 | 0.799847 | -0.184882 | 0.797312 | 0.761256 | 0.345736 |
| 524 | El Salvador | 2017 | 6.339318 | 9.042402 | 0.828953 | 65.800003 | 0.757827 | -0.171884 | 0.777749 | 0.848851 | 0.268448 |
| 525 | El Salvador | 2018 | 6.241199 | 9.061327 | 0.820300 | 66.099998 | 0.863335 | -0.095272 | 0.800700 | 0.860207 | 0.269586 |
| 526 | El Salvador | 2019 | 6.454821 | 9.079775 | 0.764391 | 66.400002 | 0.877391 | -0.108848 | 0.681576 | 0.870573 | 0.271475 |
| 527 | El Salvador | 2020 | 5.461927 | 9.018846 | 0.695624 | 66.699997 | 0.923945 | -0.126474 | 0.583036 | 0.838904 | 0.329440 |
| 528 | Estonia | 2006 | 5.371055 | 10.269773 | 0.910064 | 64.860001 | 0.748576 | -0.263854 | 0.796723 | 0.654531 | 0.215225 |
| 529 | Estonia | 2007 | 5.332044 | 10.347340 | 0.895632 | 65.320000 | 0.712121 | -0.245836 | 0.742697 | 0.665570 | 0.176231 |
| 530 | Estonia | 2008 | 5.451938 | 10.297791 | 0.903726 | 65.779999 | 0.642325 | -0.217436 | 0.662770 | 0.597254 | 0.217813 |
| 531 | Estonia | 2009 | 5.137739 | 10.143838 | 0.873775 | 66.239998 | 0.610709 | -0.229775 | 0.793152 | 0.597613 | 0.243075 |
| 532 | Estonia | 2011 | 5.486820 | 10.247500 | 0.908713 | 66.959999 | 0.735225 | -0.168138 | 0.686784 | 0.651386 | 0.205158 |
| 533 | Estonia | 2012 | 5.363928 | 10.281851 | 0.889455 | 67.220001 | 0.696826 | -0.191811 | 0.792853 | 0.647360 | 0.198967 |
| 534 | Estonia | 2013 | 5.367446 | 10.298781 | 0.900722 | 67.480003 | 0.753559 | -0.200791 | 0.726356 | 0.702256 | 0.199018 |
| 535 | Estonia | 2014 | 5.555983 | 10.330840 | 0.917102 | 67.739998 | 0.773327 | -0.152967 | 0.652447 | 0.680431 | 0.203439 |
| 536 | Estonia | 2015 | 5.628909 | 10.348465 | 0.917930 | 68.000000 | 0.814692 | -0.163681 | 0.568734 | 0.723338 | 0.182695 |
| 537 | Estonia | 2016 | 5.649675 | 10.374149 | 0.937715 | 68.199997 | 0.842771 | -0.149049 | 0.639085 | 0.726255 | 0.176869 |
| 538 | Estonia | 2017 | 5.938396 | 10.428835 | 0.935686 | 68.400002 | 0.861749 | -0.100625 | 0.668402 | 0.805218 | 0.160164 |
| 539 | Estonia | 2018 | 6.091302 | 10.471868 | 0.932694 | 68.599998 | 0.885618 | -0.141337 | 0.620678 | 0.794730 | 0.163182 |
| 540 | Estonia | 2019 | 6.034641 | 10.510816 | 0.934064 | 68.800003 | 0.886504 | -0.095724 | 0.575754 | 0.804280 | 0.156279 |
| 541 | Estonia | 2020 | 6.452564 | 10.458589 | 0.957770 | 69.000000 | 0.954201 | -0.082279 | 0.397835 | 0.806924 | 0.187679 |
| 542 | Ethiopia | 2012 | 4.561169 | 7.270575 | 0.658794 | 55.200001 | 0.776308 | -0.043737 | NaN | 0.668341 | 0.137166 |
| 543 | Ethiopia | 2013 | 4.444827 | 7.342895 | 0.602482 | 55.799999 | 0.706796 | -0.007737 | 0.750478 | 0.642846 | 0.213351 |
| 544 | Ethiopia | 2014 | 4.506647 | 7.412543 | 0.640452 | 56.400002 | 0.693559 | 0.080252 | 0.701800 | 0.737837 | 0.302858 |
| 545 | Ethiopia | 2015 | 4.573155 | 7.483854 | 0.625597 | 57.000000 | 0.802643 | 0.112722 | 0.567027 | 0.713888 | 0.236629 |
| 546 | Ethiopia | 2016 | 4.297849 | 7.546919 | 0.718719 | 57.500000 | 0.744308 | 0.038447 | 0.702881 | 0.727071 | 0.253941 |
| 547 | Ethiopia | 2017 | 4.180315 | 7.611625 | 0.733540 | 58.000000 | 0.717101 | 0.001413 | 0.756899 | 0.608515 | 0.304436 |
| 548 | Ethiopia | 2018 | 4.379262 | 7.651364 | 0.740155 | 58.500000 | 0.740343 | 0.039446 | 0.799466 | 0.659521 | 0.271754 |
| 549 | Ethiopia | 2019 | 4.099555 | 7.705131 | 0.748058 | 59.000000 | 0.753516 | 0.052576 | 0.731845 | 0.631182 | 0.282739 |
| 550 | Ethiopia | 2020 | 4.549220 | 7.710983 | 0.823138 | 59.500000 | 0.768694 | 0.188497 | 0.783822 | 0.669389 | 0.251514 |
| 551 | Finland | 2006 | 7.672449 | 10.745330 | 0.964563 | 69.760002 | 0.968580 | -0.004539 | 0.132430 | 0.721505 | 0.172134 |
| 552 | Finland | 2008 | 7.670627 | 10.795864 | 0.951340 | 70.080002 | 0.934179 | 0.027669 | 0.216568 | 0.772778 | 0.143539 |
| 553 | Finland | 2010 | 7.393264 | 10.733676 | 0.935481 | 70.400002 | 0.916009 | 0.091150 | 0.412516 | 0.832109 | 0.202095 |
| 554 | Finland | 2011 | 7.354225 | 10.754196 | 0.937857 | 70.639999 | 0.936448 | 0.101488 | 0.319593 | 0.772944 | 0.205239 |
| 555 | Finland | 2012 | 7.420209 | 10.735366 | 0.927739 | 70.879997 | 0.920968 | -0.001056 | 0.360734 | 0.796285 | 0.201654 |
| 556 | Finland | 2013 | 7.444636 | 10.721698 | 0.940869 | 71.120003 | 0.918625 | 0.039570 | 0.305770 | 0.768957 | 0.194673 |
| 557 | Finland | 2014 | 7.384571 | 10.713906 | 0.952017 | 71.360001 | 0.933044 | -0.000784 | 0.265480 | 0.784110 | 0.198814 |
| 558 | Finland | 2015 | 7.447926 | 10.716033 | 0.947801 | 71.599998 | 0.929862 | 0.111265 | 0.223370 | 0.751316 | 0.191058 |
| 559 | Finland | 2016 | 7.659843 | 10.739903 | 0.953940 | 71.699997 | 0.948372 | -0.026774 | 0.249660 | 0.797325 | 0.181998 |
| 560 | Finland | 2017 | 7.788252 | 10.768089 | 0.963826 | 71.800003 | 0.962199 | -0.002134 | 0.192413 | 0.787137 | 0.176066 |
| 561 | Finland | 2018 | 7.858107 | 10.782932 | 0.962155 | 71.900002 | 0.937807 | -0.127380 | 0.198605 | 0.781546 | 0.181781 |
| 562 | Finland | 2019 | 7.780348 | 10.791813 | 0.937416 | 72.000000 | 0.947617 | -0.051525 | 0.195338 | 0.755210 | 0.180733 |
| 563 | Finland | 2020 | 7.889350 | 10.750446 | 0.961621 | 72.099998 | 0.962424 | -0.115532 | 0.163636 | 0.744292 | 0.192898 |
| 564 | France | 2005 | 7.093393 | 10.641690 | 0.940338 | 71.300003 | 0.894819 | NaN | 0.687851 | 0.768988 | 0.225094 |
| 565 | France | 2006 | 6.582700 | 10.658916 | 0.943929 | 71.480003 | 0.789121 | 0.126045 | 0.699270 | 0.777402 | 0.288682 |
| 566 | France | 2008 | 7.008065 | 10.673645 | 0.935351 | 71.839996 | 0.833327 | -0.031021 | 0.668876 | 0.745672 | 0.280619 |
| 567 | France | 2009 | 6.283498 | 10.639346 | 0.918159 | 72.019997 | 0.798213 | -0.081896 | 0.654168 | 0.762939 | 0.303367 |
| 568 | France | 2010 | 6.797901 | 10.653713 | 0.942955 | 72.199997 | 0.849702 | -0.103513 | 0.622954 | 0.789724 | 0.260568 |
| 569 | France | 2011 | 6.959185 | 10.670567 | 0.921286 | 72.400002 | 0.903367 | -0.102445 | 0.626625 | 0.780809 | 0.280995 |
| 570 | France | 2012 | 6.649365 | 10.668853 | 0.937097 | 72.599998 | 0.841320 | -0.149065 | 0.607905 | 0.754120 | 0.252988 |
| 571 | France | 2013 | 6.667121 | 10.669452 | 0.907691 | 72.800003 | 0.877796 | -0.124514 | 0.699069 | 0.800136 | 0.204970 |
| 572 | France | 2014 | 6.466868 | 10.674232 | 0.877505 | 73.000000 | 0.803474 | -0.118097 | 0.655637 | 0.811054 | 0.215894 |
| 573 | France | 2015 | 6.357625 | 10.681743 | 0.895719 | 73.199997 | 0.817036 | -0.139271 | 0.640602 | 0.785966 | 0.215400 |
| 574 | France | 2016 | 6.475209 | 10.690000 | 0.884923 | 73.400002 | 0.786780 | -0.091287 | 0.622697 | 0.772661 | 0.270036 |
| 575 | France | 2017 | 6.635222 | 10.710555 | 0.931495 | 73.599998 | 0.833890 | -0.123433 | 0.601486 | 0.762098 | 0.241984 |
| 576 | France | 2018 | 6.665904 | 10.726808 | 0.921463 | 73.800003 | 0.816377 | -0.137875 | 0.581775 | 0.767313 | 0.282451 |
| 577 | France | 2019 | 6.689644 | 10.740378 | 0.958348 | 74.000000 | 0.827241 | -0.133166 | 0.568272 | 0.735155 | 0.250416 |
| 578 | France | 2020 | 6.714112 | 10.643280 | 0.947354 | 74.199997 | 0.823386 | -0.168961 | 0.564641 | 0.731814 | 0.230950 |
| 579 | Gabon | 2011 | 4.255401 | 9.607934 | 0.652702 | 55.480000 | 0.771872 | -0.211380 | 0.850831 | 0.591381 | 0.263955 |
| 580 | Gabon | 2012 | 3.972059 | 9.621227 | 0.736096 | 56.160000 | 0.565966 | -0.195044 | 0.810120 | 0.469999 | 0.265743 |
| 581 | Gabon | 2013 | 3.800287 | 9.638289 | 0.733488 | 56.840000 | 0.682490 | -0.145539 | 0.780439 | 0.509571 | 0.287097 |
| 582 | Gabon | 2014 | 3.918073 | 9.644469 | 0.828597 | 57.520000 | 0.606614 | -0.197952 | 0.781658 | 0.539161 | 0.293042 |
| 583 | Gabon | 2015 | 4.661013 | 9.649174 | 0.755862 | 58.200001 | 0.671301 | -0.193561 | 0.866777 | 0.626362 | 0.371656 |
| 584 | Gabon | 2016 | 4.831764 | 9.639439 | 0.780049 | 58.700001 | 0.698942 | -0.204033 | 0.816564 | 0.640117 | 0.432405 |
| 585 | Gabon | 2017 | 4.782383 | 9.616257 | 0.806941 | 59.200001 | 0.652360 | -0.228041 | 0.868306 | 0.634047 | 0.446124 |
| 586 | Gabon | 2018 | 4.783009 | 9.598550 | 0.784828 | 59.700001 | 0.719135 | -0.196936 | 0.822863 | 0.640692 | 0.417661 |
| 587 | Gabon | 2019 | 4.914393 | 9.607087 | 0.763052 | 60.200001 | 0.736350 | -0.202520 | 0.846254 | 0.692702 | 0.412961 |
| 588 | Gambia | 2017 | 4.117939 | 7.636584 | 0.697002 | 54.700001 | 0.812326 | 0.110878 | 0.571616 | 0.838287 | 0.277247 |
| 589 | Gambia | 2018 | 4.922099 | 7.670534 | 0.684800 | 55.000000 | 0.718729 | 0.440160 | 0.691070 | 0.804012 | 0.379208 |
| 590 | Gambia | 2019 | 5.163627 | 7.699350 | 0.693870 | 55.299999 | 0.676595 | 0.410180 | 0.798108 | 0.772816 | 0.400723 |
| 591 | Georgia | 2006 | 3.675108 | 8.993416 | 0.646636 | 65.120003 | 0.552593 | -0.267064 | 0.751934 | 0.433115 | 0.269384 |
| 592 | Georgia | 2007 | 3.707195 | 9.117117 | 0.548369 | 65.040001 | 0.463723 | -0.266687 | 0.697340 | 0.426648 | 0.235847 |
| 593 | Georgia | 2008 | 4.156090 | 9.144053 | 0.607513 | 64.959999 | 0.613997 | -0.224274 | 0.497999 | 0.440980 | 0.261508 |
| 594 | Georgia | 2009 | 3.800639 | 9.115746 | 0.543513 | 64.879997 | 0.495314 | -0.232556 | 0.534585 | 0.491961 | 0.242350 |
| 595 | Georgia | 2010 | 4.101837 | 9.183661 | 0.540389 | 64.800003 | 0.557858 | -0.247611 | 0.459736 | 0.501790 | 0.242536 |
| 596 | Georgia | 2011 | 4.203031 | 9.263072 | 0.502937 | 64.860001 | 0.632465 | -0.254860 | 0.353346 | 0.514921 | 0.246770 |
| 597 | Georgia | 2012 | 4.254446 | 9.332182 | 0.532586 | 64.919998 | 0.658724 | -0.268965 | 0.320888 | 0.559154 | 0.250088 |
| 598 | Georgia | 2013 | 4.348921 | 9.370765 | 0.559166 | 64.980003 | 0.722128 | -0.254065 | 0.348714 | 0.595041 | 0.199907 |
| 599 | Georgia | 2014 | 4.287508 | 9.413660 | 0.558420 | 65.040001 | 0.719781 | -0.232957 | 0.415526 | 0.569884 | 0.204328 |
| 600 | Georgia | 2015 | 4.121941 | 9.441860 | 0.517372 | 65.099998 | 0.639945 | -0.204795 | 0.502417 | 0.547280 | 0.233192 |
| 601 | Georgia | 2016 | 4.448386 | 9.469912 | 0.533412 | 64.900002 | 0.606468 | -0.249173 | 0.560924 | 0.563896 | 0.223224 |
| 602 | Georgia | 2017 | 4.450775 | 9.517068 | 0.590495 | 64.699997 | 0.820909 | -0.243887 | 0.589632 | 0.581128 | 0.209640 |
| 603 | Georgia | 2018 | 4.659097 | 9.565009 | 0.617219 | 64.500000 | 0.775144 | -0.232731 | 0.754854 | 0.572953 | 0.243779 |
| 604 | Georgia | 2019 | 4.891836 | 9.616757 | 0.674976 | 64.300003 | 0.810534 | -0.259722 | 0.647223 | 0.604491 | 0.243710 |
| 605 | Georgia | 2020 | 5.123143 | 9.569304 | 0.718346 | 64.099998 | 0.764352 | -0.221125 | 0.582735 | 0.610895 | 0.294512 |
| 606 | Germany | 2005 | 6.619550 | 10.689224 | 0.963490 | 70.199997 | 0.846624 | NaN | 0.781007 | 0.775692 | 0.197262 |
| 607 | Germany | 2007 | 6.416820 | 10.758531 | 0.925938 | 70.480003 | 0.800878 | 0.167073 | 0.792179 | 0.732469 | 0.230812 |
| 608 | Germany | 2008 | 6.521790 | 10.770008 | 0.923211 | 70.620003 | 0.765557 | NaN | 0.758266 | 0.787482 | 0.220000 |
| 609 | Germany | 2009 | 6.641493 | 10.713883 | 0.934782 | 70.760002 | 0.843785 | 0.127240 | 0.689931 | 0.791827 | 0.206445 |
| 610 | Germany | 2010 | 6.724531 | 10.756355 | 0.939309 | 70.900002 | 0.842656 | 0.095138 | 0.688006 | 0.793706 | 0.182344 |
| 611 | Germany | 2011 | 6.621312 | 10.813384 | 0.947237 | 70.980003 | 0.906293 | 0.032935 | 0.677172 | 0.793666 | 0.165200 |
| 612 | Germany | 2012 | 6.702362 | 10.815693 | 0.926407 | 71.059998 | 0.904440 | 0.071023 | 0.679237 | 0.803739 | 0.169576 |
| 613 | Germany | 2013 | 6.965125 | 10.817237 | 0.931421 | 71.139999 | 0.894313 | 0.024312 | 0.565794 | 0.743487 | 0.204996 |
| 614 | Germany | 2014 | 6.984214 | 10.835081 | 0.937559 | 71.220001 | 0.898683 | 0.087881 | 0.473953 | 0.785408 | 0.187845 |
| 615 | Germany | 2015 | 7.037138 | 10.843672 | 0.925923 | 71.300003 | 0.889429 | 0.177622 | 0.412168 | 0.764539 | 0.202705 |
| 616 | Germany | 2016 | 6.873763 | 10.857656 | 0.906029 | 71.599998 | 0.870515 | 0.148288 | 0.445922 | 0.737746 | 0.187255 |
| 617 | Germany | 2017 | 7.074325 | 10.878269 | 0.892166 | 71.900002 | 0.840728 | 0.145139 | 0.414021 | 0.736566 | 0.196435 |
| 618 | Germany | 2018 | 7.118364 | 10.890423 | 0.919763 | 72.199997 | 0.876888 | 0.033948 | 0.495674 | 0.780280 | 0.243215 |
| 619 | Germany | 2019 | 7.035472 | 10.893314 | 0.885667 | 72.500000 | 0.884752 | 0.057100 | 0.462255 | 0.750609 | 0.226171 |
| 620 | Germany | 2020 | 7.311898 | 10.833499 | 0.905080 | 72.800003 | 0.864356 | -0.060048 | 0.424089 | 0.759594 | 0.205927 |
| 621 | Ghana | 2006 | 4.535020 | 8.073256 | 0.728270 | 52.340000 | 0.849283 | 0.213096 | 0.814070 | 0.671201 | 0.197607 |
| 622 | Ghana | 2007 | 5.220148 | 8.090007 | 0.729648 | 52.779999 | 0.891153 | 0.137620 | 0.771188 | 0.685636 | 0.216630 |
| 623 | Ghana | 2008 | 4.965135 | 8.151771 | 0.622255 | 53.220001 | 0.838006 | 0.119717 | 0.862870 | 0.717010 | 0.172045 |
| 624 | Ghana | 2009 | 4.197696 | 8.173640 | 0.633198 | 53.660000 | 0.757478 | 0.005178 | 0.889738 | 0.774203 | 0.197590 |
| 625 | Ghana | 2010 | 4.606252 | 8.224802 | 0.738559 | 54.099998 | 0.891130 | 0.073658 | 0.874849 | 0.783400 | 0.184129 |
| 626 | Ghana | 2011 | 5.608200 | 8.332000 | 0.724297 | 54.480000 | 0.851896 | 0.010545 | 0.790444 | 0.743967 | 0.209213 |
| 627 | Ghana | 2012 | 5.057262 | 8.397165 | 0.685112 | 54.860001 | 0.679418 | 0.039938 | 0.897836 | 0.759688 | 0.152376 |
| 628 | Ghana | 2013 | 4.965053 | 8.444502 | 0.676289 | 55.240002 | 0.793794 | -0.065492 | 0.880178 | 0.690766 | 0.210819 |
| 629 | Ghana | 2014 | 3.860351 | 8.450147 | 0.651469 | 55.619999 | 0.676916 | 0.001083 | 0.912682 | 0.696155 | 0.280321 |
| 630 | Ghana | 2015 | 3.985916 | 8.449007 | 0.687449 | 56.000000 | 0.852016 | -0.038347 | 0.945436 | 0.689778 | 0.265279 |
| 631 | Ghana | 2016 | 4.514411 | 8.460438 | 0.647303 | 56.400002 | 0.751168 | 0.089574 | 0.893955 | 0.668264 | 0.304910 |
| 632 | Ghana | 2017 | 5.481311 | 8.516521 | 0.669111 | 56.799999 | 0.783046 | 0.078707 | 0.838610 | 0.702512 | 0.247519 |
| 633 | Ghana | 2018 | 5.003693 | 8.555344 | 0.760717 | 57.200001 | 0.816680 | 0.062165 | 0.846328 | 0.746900 | 0.250001 |
| 634 | Ghana | 2019 | 4.966810 | 8.596490 | 0.746248 | 57.599998 | 0.787448 | 0.115958 | 0.856666 | 0.682172 | 0.269940 |
| 635 | Ghana | 2020 | 5.319483 | 8.589605 | 0.642703 | 58.000000 | 0.823720 | 0.199632 | 0.847025 | 0.712766 | 0.252728 |
| 636 | Greece | 2005 | 6.006310 | 10.461699 | 0.836539 | 70.500000 | 0.734172 | NaN | 0.860563 | 0.691998 | 0.263643 |
| 637 | Greece | 2007 | 6.646961 | 10.543345 | 0.808003 | 70.900002 | 0.575309 | -0.190359 | 0.844571 | 0.737924 | 0.221744 |
| 638 | Greece | 2009 | 6.038575 | 10.490745 | 0.793318 | 71.300003 | 0.443108 | -0.293052 | 0.958768 | 0.648514 | 0.253589 |
| 639 | Greece | 2010 | 5.839559 | 10.433106 | 0.868422 | 71.500000 | 0.484111 | -0.302877 | 0.954114 | 0.633947 | 0.291516 |
| 640 | Greece | 2011 | 5.372040 | 10.338819 | 0.851555 | 71.559998 | 0.528126 | -0.316439 | 0.941153 | 0.591372 | 0.322791 |
| 641 | Greece | 2012 | 5.096354 | 10.268419 | 0.812141 | 71.620003 | 0.372610 | -0.304908 | 0.958909 | 0.580688 | 0.351506 |
| 642 | Greece | 2013 | 4.720251 | 10.242719 | 0.686650 | 71.680000 | 0.425967 | -0.272042 | 0.941310 | 0.689162 | 0.482183 |
| 643 | Greece | 2014 | 4.756237 | 10.256751 | 0.832333 | 71.739998 | 0.369156 | -0.287930 | 0.930214 | 0.694676 | 0.385433 |
| 644 | Greece | 2015 | 5.622519 | 10.258951 | 0.834825 | 71.800003 | 0.531736 | -0.271978 | 0.823960 | 0.739751 | 0.277413 |
| 645 | Greece | 2016 | 5.302619 | 10.261199 | 0.802606 | 72.000000 | 0.481617 | -0.260160 | 0.898471 | 0.700504 | 0.336208 |
| 646 | Greece | 2017 | 5.148242 | 10.278116 | 0.752900 | 72.199997 | 0.438300 | -0.290053 | 0.872239 | 0.602939 | 0.332831 |
| 647 | Greece | 2018 | 5.409289 | 10.299304 | 0.793501 | 72.400002 | 0.564456 | -0.335040 | 0.860302 | 0.665699 | 0.255007 |
| 648 | Greece | 2019 | 5.952157 | 10.319384 | 0.890810 | 72.599998 | 0.613584 | -0.288678 | 0.848004 | 0.667514 | 0.235946 |
| 649 | Greece | 2020 | 5.787616 | 10.214580 | 0.778537 | 72.800003 | 0.564614 | -0.240806 | 0.764325 | 0.684458 | 0.321684 |
| 650 | Guatemala | 2006 | 5.901429 | 8.849806 | 0.830442 | 60.740002 | 0.663382 | 0.172222 | 0.706096 | 0.818015 | 0.287082 |
| 651 | Guatemala | 2007 | 6.329581 | 8.891179 | 0.866397 | 61.080002 | 0.627587 | 0.135808 | 0.809743 | 0.819046 | 0.224380 |
| 652 | Guatemala | 2008 | 6.414495 | 8.904189 | 0.865605 | 61.419998 | 0.630152 | 0.205520 | 0.796285 | 0.834360 | 0.233636 |
| 653 | Guatemala | 2009 | 6.451916 | 8.890625 | 0.833816 | 61.759998 | 0.643479 | 0.196545 | 0.754889 | 0.828716 | 0.239742 |
| 654 | Guatemala | 2010 | 6.289749 | 8.900550 | 0.859052 | 62.099998 | 0.695863 | 0.166235 | 0.794835 | 0.849933 | 0.235618 |
| 655 | Guatemala | 2011 | 5.743354 | 8.923133 | 0.768112 | 62.459999 | 0.762963 | 0.008882 | 0.863039 | 0.844494 | 0.289358 |
| 656 | Guatemala | 2012 | 5.855717 | 8.934624 | 0.802149 | 62.820000 | 0.865472 | 0.020275 | 0.820924 | 0.862783 | 0.349405 |
| 657 | Guatemala | 2013 | 5.984601 | 8.953361 | 0.829650 | 63.180000 | 0.884005 | 0.044932 | 0.816770 | 0.866774 | 0.332524 |
| 658 | Guatemala | 2014 | 6.536031 | 8.979554 | 0.833975 | 63.540001 | 0.843399 | 0.107526 | 0.804463 | 0.835368 | 0.305115 |
| 659 | Guatemala | 2015 | 6.464987 | 9.002746 | 0.822837 | 63.900002 | 0.868640 | 0.051297 | 0.821655 | 0.851371 | 0.310554 |
| 660 | Guatemala | 2016 | 6.358916 | 9.012591 | 0.811235 | 64.199997 | 0.862676 | 0.011463 | 0.812030 | 0.846123 | 0.321357 |
| 661 | Guatemala | 2017 | 6.325119 | 9.026101 | 0.826492 | 64.500000 | 0.914522 | -0.058531 | 0.799748 | 0.845866 | 0.308086 |
| 662 | Guatemala | 2018 | 6.626592 | 9.041739 | 0.841107 | 64.800003 | 0.909538 | -0.010064 | 0.765454 | 0.871362 | 0.262411 |
| 663 | Guatemala | 2019 | 6.262175 | 9.063875 | 0.774074 | 65.099998 | 0.900676 | -0.062303 | 0.772578 | 0.859413 | 0.310789 |
| 664 | Guinea | 2011 | 4.044569 | 7.567404 | 0.598466 | 50.220001 | 0.796830 | 0.040658 | 0.743256 | 0.700549 | 0.260133 |
| 665 | Guinea | 2012 | 3.651555 | 7.602896 | 0.542295 | 50.439999 | 0.646188 | 0.000928 | 0.794450 | 0.677213 | 0.284573 |
| 666 | Guinea | 2013 | 3.901793 | 7.619241 | 0.566867 | 50.660000 | 0.692737 | 0.090948 | 0.815482 | 0.600325 | 0.348057 |
| 667 | Guinea | 2014 | 3.412483 | 7.632116 | 0.637714 | 50.880001 | 0.683558 | 0.005991 | 0.705246 | 0.628650 | 0.351265 |
| 668 | Guinea | 2015 | 3.504694 | 7.644764 | 0.578860 | 51.099998 | 0.665953 | 0.006547 | 0.762152 | 0.666971 | 0.267741 |
| 669 | Guinea | 2016 | 3.602855 | 7.721042 | 0.675447 | 52.200001 | 0.725685 | -0.056312 | 0.802781 | 0.686985 | 0.374394 |
| 670 | Guinea | 2017 | 4.873723 | 7.791771 | 0.634026 | 53.299999 | 0.738213 | 0.037824 | 0.750026 | 0.704477 | 0.422461 |
| 671 | Guinea | 2018 | 5.252227 | 7.823416 | 0.630433 | 54.400002 | 0.731157 | 0.092035 | 0.778394 | 0.743881 | 0.440438 |
| 672 | Guinea | 2019 | 4.767684 | 7.849340 | 0.655124 | 55.500000 | 0.691399 | 0.096817 | 0.755585 | 0.684647 | 0.473388 |
| 673 | Guyana | 2007 | 5.992826 | 8.773289 | 0.848765 | 57.259998 | 0.694006 | 0.110037 | 0.835569 | 0.767541 | 0.296420 |
| 674 | Haiti | 2006 | 3.754156 | 7.407168 | 0.693801 | 48.459999 | 0.449475 | 0.400810 | 0.853506 | 0.612906 | 0.332141 |
| 675 | Haiti | 2008 | 3.846329 | 7.416673 | 0.679098 | 40.380001 | 0.464971 | 0.260972 | 0.811659 | 0.607697 | 0.255774 |
| 676 | Haiti | 2010 | 3.765999 | 7.384417 | 0.554031 | 32.299999 | 0.372941 | 0.215561 | 0.848007 | 0.554960 | 0.292557 |
| 677 | Haiti | 2011 | 4.844574 | 7.423120 | 0.567039 | 36.860001 | 0.412588 | 0.242585 | 0.681960 | 0.625240 | 0.244856 |
| 678 | Haiti | 2012 | 4.413475 | 7.436831 | 0.748663 | 41.419998 | 0.482486 | 0.289061 | 0.717166 | 0.593434 | 0.283806 |
| 679 | Haiti | 2013 | 4.621962 | 7.463928 | 0.648351 | 45.980000 | 0.610410 | 0.289404 | 0.668976 | 0.538055 | 0.326656 |
| 680 | Haiti | 2014 | 3.888778 | 7.477151 | 0.554149 | 50.540001 | 0.508805 | 0.284814 | 0.707521 | 0.592565 | 0.327208 |
| 681 | Haiti | 2015 | 3.569762 | 7.475525 | 0.564320 | 55.099998 | 0.398295 | 0.305932 | 0.777404 | 0.618564 | 0.332540 |
| 682 | Haiti | 2016 | 3.352300 | 7.476534 | 0.583742 | 55.299999 | 0.303540 | 0.291313 | 0.838523 | 0.552774 | 0.367341 |
| 683 | Haiti | 2017 | 3.823866 | 7.475148 | 0.646985 | 55.500000 | 0.484429 | 0.380997 | 0.647192 | 0.573367 | 0.321693 |
| 684 | Haiti | 2018 | 3.614928 | 7.477138 | 0.537976 | 55.700001 | 0.591468 | 0.421520 | 0.720445 | 0.584113 | 0.358720 |
| 685 | Honduras | 2006 | 5.396520 | 8.462430 | 0.932677 | 64.540001 | 0.650254 | 0.089146 | 0.843539 | 0.857973 | 0.155474 |
| 686 | Honduras | 2007 | 5.097154 | 8.499909 | 0.818869 | 64.779999 | 0.675631 | 0.230320 | 0.825975 | 0.758959 | 0.198780 |
| 687 | Honduras | 2008 | 5.420331 | 8.519512 | 0.828176 | 65.019997 | 0.686881 | 0.223111 | 0.863222 | 0.789361 | 0.205854 |
| 688 | Honduras | 2009 | 6.033189 | 8.473840 | 0.823966 | 65.260002 | 0.661203 | 0.118611 | 0.856734 | 0.802866 | 0.261304 |
| 689 | Honduras | 2010 | 5.866131 | 8.490228 | 0.802939 | 65.500000 | 0.645528 | 0.105422 | 0.819940 | 0.796519 | 0.259946 |
| 690 | Honduras | 2011 | 4.961031 | 8.508435 | 0.765702 | 65.720001 | 0.783369 | 0.095479 | 0.883963 | 0.815691 | 0.307471 |
| 691 | Honduras | 2012 | 4.602218 | 8.530200 | 0.779195 | 65.940002 | 0.700452 | -0.003207 | 0.871437 | 0.846510 | 0.293591 |
| 692 | Honduras | 2013 | 4.713358 | 8.539632 | 0.791960 | 66.160004 | 0.698400 | -0.027216 | 0.867700 | 0.816519 | 0.283281 |
| 693 | Honduras | 2014 | 5.055726 | 8.552060 | 0.790215 | 66.379997 | 0.695983 | 0.015080 | 0.834350 | 0.820184 | 0.299388 |
| 694 | Honduras | 2015 | 4.845437 | 8.572327 | 0.772376 | 66.599998 | 0.534058 | -0.096824 | 0.848083 | 0.862837 | 0.310766 |
| 695 | Honduras | 2016 | 5.648155 | 8.593342 | 0.773910 | 66.800003 | 0.850047 | 0.080017 | 0.792875 | 0.832397 | 0.296847 |
| 696 | Honduras | 2017 | 6.019986 | 8.623713 | 0.843355 | 67.000000 | 0.898377 | 0.072136 | 0.783429 | 0.842201 | 0.248383 |
| 697 | Honduras | 2018 | 5.908424 | 8.643342 | 0.827067 | 67.199997 | 0.872162 | 0.099210 | 0.803565 | 0.871845 | 0.287358 |
| 698 | Honduras | 2019 | 5.930051 | 8.653117 | 0.797148 | 67.400002 | 0.846190 | 0.062709 | 0.814963 | 0.849955 | 0.278882 |
| 699 | Hong Kong S.A.R. of China | 2006 | 5.511187 | 10.746425 | 0.812178 | NaN | 0.909820 | 0.155567 | 0.355985 | 0.723260 | 0.235955 |
| 700 | Hong Kong S.A.R. of China | 2008 | 5.137262 | 10.815545 | 0.840222 | NaN | 0.922211 | 0.296268 | 0.273945 | 0.718972 | 0.236634 |
| 701 | Hong Kong S.A.R. of China | 2009 | 5.397056 | 10.788494 | 0.834716 | NaN | 0.918026 | 0.307638 | 0.272125 | 0.762151 | 0.210104 |
| 702 | Hong Kong S.A.R. of China | 2010 | 5.642835 | 10.846634 | 0.857314 | NaN | 0.890418 | 0.331955 | 0.255775 | 0.710370 | 0.183106 |
| 703 | Hong Kong S.A.R. of China | 2011 | 5.474011 | 10.886932 | 0.846060 | NaN | 0.894330 | 0.234555 | 0.244887 | 0.733887 | 0.195712 |
| 704 | Hong Kong S.A.R. of China | 2012 | 5.483765 | 10.892753 | 0.826426 | NaN | 0.879752 | 0.222402 | 0.379783 | 0.715137 | 0.183349 |
| 705 | Hong Kong S.A.R. of China | 2014 | 5.458051 | 10.939503 | 0.833558 | NaN | 0.843082 | 0.223799 | 0.422960 | 0.683968 | 0.242868 |
| 706 | Hong Kong S.A.R. of China | 2016 | 5.498421 | 10.969857 | 0.832078 | NaN | 0.799743 | 0.100235 | 0.402813 | 0.664093 | 0.213115 |
| 707 | Hong Kong S.A.R. of China | 2017 | 5.362475 | 10.999584 | 0.831066 | NaN | 0.830657 | 0.140063 | 0.415810 | 0.639533 | 0.200593 |
| 708 | Hong Kong S.A.R. of China | 2019 | 5.659317 | 11.000313 | 0.855826 | NaN | 0.726852 | 0.067344 | 0.431974 | 0.599320 | 0.357607 |
| 709 | Hong Kong S.A.R. of China | 2020 | 5.295341 | NaN | 0.812943 | NaN | 0.705452 | NaN | 0.380351 | 0.608647 | 0.210314 |
| 710 | Hungary | 2005 | 5.193933 | 10.107747 | 0.929628 | 64.599998 | 0.696874 | NaN | 0.902811 | 0.675444 | 0.290327 |
| 711 | Hungary | 2007 | 4.953917 | 10.152791 | 0.930654 | 65.000000 | 0.538498 | -0.160848 | 0.895177 | 0.700642 | 0.230283 |
| 712 | Hungary | 2009 | 4.894600 | 10.097274 | 0.900874 | 65.400002 | 0.464373 | -0.125157 | 0.914701 | 0.664400 | 0.227890 |
| 713 | Hungary | 2010 | 4.725132 | 10.106154 | 0.895694 | 65.599998 | 0.513835 | -0.145089 | 0.983276 | 0.655816 | 0.234813 |
| 714 | Hungary | 2011 | 4.917603 | 10.127015 | 0.893662 | 65.760002 | 0.631100 | -0.089036 | 0.939908 | 0.642114 | 0.304520 |
| 715 | Hungary | 2012 | 4.683358 | 10.117352 | 0.906114 | 65.919998 | 0.569232 | -0.136061 | 0.930297 | 0.651908 | 0.315398 |
| 716 | Hungary | 2013 | 4.914467 | 10.139545 | 0.877318 | 66.080002 | 0.673728 | -0.112913 | 0.911533 | 0.705704 | 0.306724 |
| 717 | Hungary | 2014 | 5.180563 | 10.183334 | 0.844735 | 66.239998 | 0.494475 | -0.149750 | 0.855361 | 0.650690 | 0.237620 |
| 718 | Hungary | 2015 | 5.344383 | 10.223448 | 0.858734 | 66.400002 | 0.557721 | -0.197823 | 0.907530 | 0.706815 | 0.244536 |
| 719 | Hungary | 2016 | 5.448902 | 10.248160 | 0.899512 | 66.800003 | 0.553952 | -0.186869 | 0.924186 | 0.665911 | 0.243326 |
| 720 | Hungary | 2017 | 6.065039 | 10.293139 | 0.876748 | 67.199997 | 0.661166 | -0.139318 | 0.886361 | 0.735184 | 0.180921 |
| 721 | Hungary | 2018 | 5.935771 | 10.344091 | 0.940591 | 67.599998 | 0.692627 | -0.242624 | 0.911277 | 0.676073 | 0.201083 |
| 722 | Hungary | 2019 | 6.000260 | 10.392768 | 0.946516 | 68.000000 | 0.798041 | -0.194903 | 0.883571 | 0.743014 | 0.180348 |
| 723 | Hungary | 2020 | 6.038050 | 10.335148 | 0.943400 | 68.400002 | 0.770968 | -0.120405 | 0.836105 | 0.735238 | 0.240052 |
| 724 | Iceland | 2008 | 6.888284 | 10.861430 | 0.977430 | 72.320000 | 0.885196 | 0.271766 | 0.708049 | 0.879538 | 0.153068 |
| 725 | Iceland | 2012 | 7.590660 | 10.777463 | 0.978965 | 72.760002 | 0.904655 | 0.241383 | 0.758586 | 0.899718 | 0.157154 |
| 726 | Iceland | 2013 | 7.501394 | 10.808511 | 0.967145 | 72.839996 | 0.923208 | 0.305916 | 0.712599 | 0.869971 | 0.156276 |
| 727 | Iceland | 2015 | 7.498071 | 10.853975 | 0.980283 | 73.000000 | 0.940485 | 0.300744 | 0.638662 | 0.849021 | 0.179504 |
| 728 | Iceland | 2016 | 7.510035 | 10.904262 | 0.984940 | 73.000000 | 0.951610 | 0.280812 | 0.719300 | 0.873888 | 0.158169 |
| 729 | Iceland | 2017 | 7.476214 | 10.925262 | 0.966753 | 73.000000 | 0.938783 | 0.245770 | 0.726845 | 0.895255 | 0.148160 |
| 730 | Iceland | 2019 | 7.532505 | 10.930854 | 0.981825 | 73.000000 | 0.959470 | NaN | 0.698708 | 0.836009 | 0.177704 |
| 731 | Iceland | 2020 | 7.575490 | 10.824201 | 0.983286 | 73.000000 | 0.948627 | 0.160274 | 0.644064 | 0.863018 | 0.171795 |
| 732 | India | 2006 | 5.348259 | 8.145189 | 0.707318 | 55.720001 | 0.773737 | NaN | 0.854812 | 0.687017 | 0.198602 |
| 733 | India | 2007 | 5.026793 | 8.203913 | 0.568993 | 56.139999 | 0.728893 | -0.051251 | 0.862143 | 0.668468 | 0.252502 |
| 734 | India | 2008 | 5.145833 | 8.219664 | 0.683593 | 56.560001 | 0.755840 | -0.071906 | 0.891188 | 0.674160 | 0.259315 |
| 735 | India | 2009 | 4.521518 | 8.281240 | 0.652852 | 56.980000 | 0.678644 | -0.025930 | 0.894611 | 0.771343 | 0.300621 |
| 736 | India | 2010 | 4.989277 | 8.349294 | 0.604810 | 57.400002 | 0.783060 | 0.057902 | 0.862548 | 0.696512 | 0.266502 |
| 737 | India | 2011 | 4.634871 | 8.387494 | 0.552593 | 57.700001 | 0.837552 | -0.037767 | 0.907794 | 0.648167 | 0.231594 |
| 738 | India | 2012 | 4.720147 | 8.428305 | 0.510575 | 58.000000 | 0.609320 | 0.067322 | 0.829615 | 0.628734 | 0.294841 |
| 739 | India | 2013 | 4.427789 | 8.478379 | 0.552826 | 58.299999 | 0.740177 | 0.084251 | 0.832356 | 0.679958 | 0.330437 |
| 740 | India | 2014 | 4.424379 | 8.538408 | 0.621467 | 58.599998 | 0.809383 | -0.025796 | 0.832142 | 0.711024 | 0.284582 |
| 741 | India | 2015 | 4.342079 | 8.604168 | 0.610133 | 58.900002 | 0.777225 | -0.005146 | 0.776435 | 0.700677 | 0.321829 |
| 742 | India | 2016 | 4.179177 | 8.672601 | 0.613529 | 59.299999 | 0.820069 | 0.045910 | 0.764722 | 0.694504 | 0.345681 |
| 743 | India | 2017 | 4.046111 | 8.730042 | 0.606767 | 59.700001 | 0.885850 | -0.041828 | 0.780803 | 0.682091 | 0.317937 |
| 744 | India | 2018 | 3.818069 | 8.779066 | 0.638052 | 60.099998 | 0.890443 | 0.084721 | 0.805263 | 0.657287 | 0.357458 |
| 745 | India | 2019 | 3.248770 | 8.817933 | 0.560781 | 60.500000 | 0.875540 | 0.111779 | 0.751979 | 0.647752 | 0.466336 |
| 746 | India | 2020 | 4.225281 | 8.702772 | 0.616639 | 60.900002 | 0.906391 | 0.074824 | 0.780124 | 0.752434 | 0.383163 |
| 747 | Indonesia | 2006 | 4.946978 | 8.850008 | 0.770951 | 59.840000 | 0.713171 | 0.347461 | 0.915120 | 0.824656 | 0.265537 |
| 748 | Indonesia | 2007 | 5.101214 | 8.898289 | 0.703788 | 59.980000 | 0.603260 | 0.311470 | 0.959867 | 0.811749 | 0.241613 |
| 749 | Indonesia | 2008 | 4.815310 | 8.943453 | 0.675075 | 60.119999 | 0.595633 | 0.164236 | 0.968212 | 0.773841 | 0.239271 |
| 750 | Indonesia | 2009 | 5.472361 | 8.975410 | 0.779368 | 60.259998 | 0.783793 | 0.190771 | 0.910941 | 0.864888 | 0.192704 |
| 751 | Indonesia | 2010 | 5.457299 | 9.022411 | 0.816022 | 60.400002 | 0.699658 | 0.447515 | 0.954050 | 0.836675 | 0.217908 |
| 752 | Indonesia | 2011 | 5.172608 | 9.068801 | 0.824977 | 60.619999 | 0.878287 | 0.437941 | 0.962295 | 0.863815 | 0.273416 |
| 753 | Indonesia | 2012 | 5.367774 | 9.113834 | 0.833621 | 60.840000 | 0.770319 | 0.354085 | 0.961589 | 0.896927 | 0.228980 |
| 754 | Indonesia | 2013 | 5.292238 | 9.154508 | 0.793761 | 61.060001 | 0.780691 | 0.376006 | 0.972669 | 0.892942 | 0.249146 |
| 755 | Indonesia | 2014 | 5.597375 | 9.190253 | 0.904828 | 61.279999 | 0.719413 | 0.407956 | 0.970144 | 0.852419 | 0.241678 |
| 756 | Indonesia | 2015 | 5.042800 | 9.225190 | 0.809478 | 61.500000 | 0.779418 | 0.471330 | 0.945967 | 0.876233 | 0.274292 |
| 757 | Indonesia | 2016 | 5.136325 | 9.262097 | 0.791831 | 61.700001 | 0.829942 | 0.499780 | 0.889677 | 0.832812 | 0.341574 |
| 758 | Indonesia | 2017 | 5.098402 | 9.299801 | 0.795589 | 61.900002 | 0.865026 | 0.487873 | 0.900416 | 0.862584 | 0.319172 |
| 759 | Indonesia | 2018 | 5.340296 | 9.338868 | 0.809379 | 62.099998 | 0.879374 | 0.511993 | 0.867729 | 0.863718 | 0.295987 |
| 760 | Indonesia | 2019 | 5.346513 | 9.376888 | 0.801918 | 62.299999 | 0.865859 | 0.555348 | 0.860785 | 0.876714 | 0.301703 |
| 761 | Iran | 2005 | 5.308190 | 9.392513 | 0.765978 | 62.000000 | 0.651168 | NaN | 0.636490 | 0.608226 | 0.456109 |
| 762 | Iran | 2007 | 5.336371 | 9.497391 | 0.717592 | 62.759998 | 0.532620 | 0.055538 | 0.871644 | 0.625507 | 0.361320 |
| 763 | Iran | 2008 | 5.128988 | 9.488964 | 0.632629 | 63.139999 | 0.601222 | 0.052281 | 0.868343 | 0.624161 | 0.345182 |
| 764 | Iran | 2011 | 4.767507 | 9.547193 | 0.582237 | 64.139999 | 0.797574 | 0.200392 | 0.664582 | 0.578114 | 0.359068 |
| 765 | Iran | 2012 | 4.608928 | 9.457778 | 0.599543 | 64.379997 | 0.764418 | NaN | 0.677707 | 0.608598 | 0.524969 |
| 766 | Iran | 2013 | 5.139579 | 9.443441 | 0.663707 | 64.620003 | 0.730215 | 0.215557 | 0.685038 | 0.659088 | 0.551840 |
| 767 | Iran | 2014 | 4.682224 | 9.475666 | 0.644064 | 64.860001 | 0.766823 | 0.240678 | 0.639682 | 0.618345 | 0.511569 |
| 768 | Iran | 2015 | 4.749956 | 9.449208 | 0.572407 | 65.099998 | 0.780383 | 0.176360 | 0.698951 | 0.644849 | 0.519858 |
| 769 | Iran | 2016 | 4.652731 | 9.561364 | 0.566281 | 65.400002 | 0.773304 | 0.185618 | 0.712783 | 0.686765 | 0.525877 |
| 770 | Iran | 2017 | 4.716783 | 9.584374 | 0.714233 | 65.699997 | 0.730635 | 0.218477 | 0.714941 | 0.693666 | 0.438534 |
| 771 | Iran | 2018 | 4.278118 | NaN | 0.673765 | 66.000000 | 0.603320 | NaN | 0.703440 | 0.553197 | 0.493149 |
| 772 | Iran | 2019 | 5.006146 | NaN | 0.698293 | 66.300003 | 0.623282 | NaN | 0.728307 | 0.600486 | 0.448526 |
| 773 | Iran | 2020 | 4.864528 | NaN | 0.757219 | 66.599998 | 0.599594 | NaN | 0.709902 | 0.582421 | 0.470245 |
| 774 | Iraq | 2008 | 4.589845 | 9.063396 | 0.744366 | 58.320000 | 0.385769 | -0.061305 | 0.909882 | 0.525002 | 0.448169 |
| 775 | Iraq | 2009 | 4.775317 | 9.076148 | 0.861746 | 58.959999 | 0.431468 | -0.199414 | 0.854340 | 0.522806 | 0.403820 |
| 776 | Iraq | 2010 | 5.065462 | 9.112019 | 0.854118 | 59.599998 | 0.419064 | -0.124621 | 0.858735 | 0.541775 | 0.430934 |
| 777 | Iraq | 2011 | 4.725366 | 9.152244 | 0.750749 | 59.360001 | 0.347414 | -0.069558 | 0.780027 | 0.487619 | 0.557099 |
| 778 | Iraq | 2012 | 4.659509 | 9.245508 | 0.730118 | 59.119999 | 0.314565 | -0.020207 | 0.789191 | 0.422928 | 0.449059 |
| 779 | Iraq | 2013 | 4.725017 | 9.279796 | 0.728285 | 58.880001 | NaN | -0.049836 | 0.709726 | NaN | 0.554279 |
| 780 | Iraq | 2014 | 4.541502 | 9.249623 | 0.725151 | 58.639999 | 0.646007 | -0.001022 | 0.726008 | 0.573671 | 0.563631 |
| 781 | Iraq | 2015 | 4.493377 | 9.240935 | 0.684435 | 58.400002 | 0.599460 | 0.019455 | 0.762167 | 0.490033 | 0.581267 |
| 782 | Iraq | 2016 | 4.412537 | 9.353771 | 0.718957 | 59.000000 | 0.666160 | -0.052077 | 0.798866 | 0.488692 | 0.569758 |
| 783 | Iraq | 2017 | 4.462399 | 9.303099 | 0.695109 | 59.599998 | 0.627722 | -0.000484 | 0.757109 | 0.505289 | 0.590539 |
| 784 | Iraq | 2018 | 4.886401 | 9.274262 | 0.763509 | 60.200001 | 0.597823 | -0.068258 | 0.886700 | 0.605323 | 0.482027 |
| 785 | Iraq | 2020 | 4.785165 | 9.167186 | 0.707847 | 61.400002 | 0.700215 | -0.020748 | 0.849109 | 0.644464 | 0.531539 |
| 786 | Ireland | 2006 | 7.144247 | 10.971882 | 0.967041 | 70.139999 | 0.943275 | 0.241917 | 0.472849 | 0.878256 | 0.208634 |
| 787 | Ireland | 2008 | 7.568030 | 10.928620 | 0.982522 | 70.820000 | 0.894109 | 0.321945 | 0.486995 | 0.875384 | 0.147759 |
| 788 | Ireland | 2009 | 7.045911 | 10.866337 | 0.958702 | 71.160004 | 0.834730 | 0.315237 | 0.579600 | 0.862124 | 0.232699 |
| 789 | Ireland | 2010 | 7.257390 | 10.878826 | 0.972886 | 71.500000 | 0.856030 | 0.347998 | 0.618024 | 0.875983 | 0.200655 |
| 790 | Ireland | 2011 | 7.006904 | 10.877893 | 0.977378 | 71.599998 | 0.952034 | 0.383449 | 0.589913 | 0.865225 | 0.190309 |
| 791 | Ireland | 2012 | 6.964645 | 10.875911 | 0.961786 | 71.699997 | 0.902195 | 0.302251 | 0.572632 | 0.835202 | 0.236662 |
| 792 | Ireland | 2013 | 6.760085 | 10.884071 | 0.955188 | 71.800003 | 0.883772 | 0.331424 | 0.558394 | 0.814345 | 0.245268 |
| 793 | Ireland | 2014 | 7.018379 | 10.958863 | 0.967745 | 71.900002 | 0.921630 | 0.263642 | 0.406036 | 0.784335 | 0.228723 |
| 794 | Ireland | 2015 | 6.830125 | 11.173858 | 0.952943 | 72.000000 | 0.892277 | 0.232601 | 0.408757 | 0.799320 | 0.225349 |
| 795 | Ireland | 2016 | 7.040731 | 11.198688 | 0.958144 | 72.099998 | 0.874589 | 0.174270 | 0.398544 | 0.809203 | 0.211063 |
| 796 | Ireland | 2017 | 7.060155 | 11.266106 | 0.943482 | 72.199997 | 0.905341 | 0.216474 | 0.337085 | 0.833389 | 0.212784 |
| 797 | Ireland | 2018 | 6.962336 | 11.332250 | 0.937862 | 72.300003 | 0.861472 | 0.144194 | 0.362210 | 0.810857 | 0.213050 |
| 798 | Ireland | 2019 | 7.254841 | 11.371147 | 0.943726 | 72.400002 | 0.892459 | 0.073613 | 0.372804 | 0.807015 | 0.223300 |
| 799 | Ireland | 2020 | 7.034931 | 11.322803 | 0.960311 | 72.500000 | 0.882098 | 0.013817 | 0.355633 | 0.796661 | 0.246447 |
| 800 | Israel | 2006 | 7.173417 | 10.389376 | 0.927079 | 71.120003 | 0.816653 | NaN | 0.905375 | 0.696438 | 0.308496 |
| 801 | Israel | 2007 | 6.841115 | 10.427745 | 0.868217 | 71.440002 | 0.682864 | 0.219236 | 0.867821 | 0.695740 | 0.319894 |
| 802 | Israel | 2008 | 7.261261 | 10.439504 | 0.859264 | 71.760002 | 0.662969 | 0.138600 | 0.898196 | 0.709695 | 0.349395 |
| 803 | Israel | 2009 | 7.352979 | 10.424802 | 0.936573 | 72.080002 | 0.592530 | 0.171667 | 0.922718 | 0.695399 | 0.326584 |
| 804 | Israel | 2010 | 7.358916 | 10.461033 | 0.881830 | 72.400002 | 0.561478 | 0.149889 | 0.902183 | 0.679458 | 0.362394 |
| 805 | Israel | 2011 | 7.433148 | 10.489279 | 0.892697 | 72.459999 | 0.722269 | 0.140867 | 0.891295 | 0.737907 | 0.384475 |
| 806 | Israel | 2012 | 7.110855 | 10.493138 | 0.903416 | 72.519997 | 0.681439 | 0.152813 | 0.862327 | 0.665102 | 0.319231 |
| 807 | Israel | 2013 | 7.320563 | 10.515121 | 0.908516 | 72.580002 | 0.739002 | 0.150384 | 0.848538 | 0.697946 | 0.408576 |
| 808 | Israel | 2014 | 7.400570 | 10.532819 | 0.889070 | 72.639999 | 0.706975 | 0.093551 | 0.818040 | 0.604293 | 0.271256 |
| 809 | Israel | 2015 | 7.079411 | 10.535648 | 0.864130 | 72.699997 | 0.752784 | 0.108476 | 0.789430 | 0.696548 | 0.256258 |
| 810 | Israel | 2016 | 7.159011 | 10.555093 | 0.889661 | 72.900002 | 0.772297 | 0.153160 | 0.804057 | 0.629189 | 0.263090 |
| 811 | Israel | 2017 | 7.331036 | 10.570462 | 0.916441 | 73.099998 | 0.768076 | 0.145330 | 0.792652 | 0.673591 | 0.276443 |
| 812 | Israel | 2018 | 6.927179 | 10.585150 | 0.909595 | 73.300003 | 0.724662 | 0.055274 | 0.770135 | 0.663490 | 0.282063 |
| 813 | Israel | 2019 | 7.331780 | 10.600675 | 0.946011 | 73.500000 | 0.834492 | 0.085437 | 0.742868 | 0.634593 | 0.265892 |
| 814 | Israel | 2020 | 7.194928 | 10.538054 | 0.959072 | 73.699997 | 0.831316 | -0.049372 | 0.747639 | 0.621398 | 0.242826 |
| 815 | Italy | 2005 | 6.853784 | 10.702738 | 0.928001 | 71.900002 | 0.802195 | NaN | 0.943912 | 0.678837 | 0.294698 |
| 816 | Italy | 2007 | 6.574412 | 10.727192 | 0.912292 | 72.260002 | 0.684297 | 0.113494 | 0.922197 | 0.715646 | 0.303446 |
| 817 | Italy | 2008 | 6.779774 | 10.710900 | 0.879663 | 72.440002 | 0.543077 | 0.049271 | 0.945625 | 0.636669 | 0.267581 |
| 818 | Italy | 2009 | 6.333800 | 10.652089 | 0.880313 | 72.620003 | 0.700550 | 0.240435 | 0.889985 | 0.775457 | 0.279378 |
| 819 | Italy | 2010 | 6.354238 | 10.666001 | 0.872384 | 72.800003 | 0.737739 | -0.059522 | 0.921075 | 0.596381 | 0.235880 |
| 820 | Italy | 2011 | 6.057086 | 10.671329 | 0.913309 | 72.839996 | 0.567738 | -0.017811 | 0.933461 | 0.658394 | 0.265568 |
| 821 | Italy | 2012 | 5.839314 | 10.638372 | 0.869487 | 72.879997 | 0.570095 | 0.112832 | 0.908324 | 0.669761 | 0.387652 |
| 822 | Italy | 2013 | 6.009374 | 10.608197 | 0.916296 | 72.919998 | 0.499169 | -0.102297 | 0.942639 | 0.778827 | 0.356616 |
| 823 | Italy | 2014 | 6.026585 | 10.598977 | 0.897899 | 72.959999 | 0.623531 | -0.064877 | 0.919960 | 0.716064 | 0.356020 |
| 824 | Italy | 2015 | 5.847684 | 10.607694 | 0.908987 | 73.000000 | 0.574766 | -0.064207 | 0.912753 | 0.691772 | 0.329209 |
| 825 | Italy | 2016 | 5.954524 | 10.622244 | 0.927213 | 73.199997 | 0.623742 | -0.080541 | 0.902801 | 0.685423 | 0.339174 |
| 826 | Italy | 2017 | 6.198870 | 10.640284 | 0.919791 | 73.400002 | 0.632843 | -0.035053 | 0.866668 | 0.661181 | 0.322846 |
| 827 | Italy | 2018 | 6.516527 | 10.650134 | 0.912656 | 73.599998 | 0.650009 | -0.021211 | 0.887825 | 0.649023 | 0.402975 |
| 828 | Italy | 2019 | 6.445417 | 10.655202 | 0.838402 | 73.800003 | 0.709479 | -0.081561 | 0.865528 | 0.631080 | 0.327960 |
| 829 | Italy | 2020 | 6.488356 | 10.562572 | 0.889824 | 74.000000 | 0.718155 | -0.149937 | 0.844095 | 0.670213 | 0.311002 |
| 830 | Ivory Coast | 2009 | 4.197182 | 8.208836 | 0.667009 | 45.779999 | 0.759862 | -0.153323 | 0.902262 | 0.603942 | 0.186184 |
| 831 | Ivory Coast | 2013 | 3.739366 | 8.274495 | 0.708571 | 47.099998 | 0.739193 | -0.030705 | 0.691118 | 0.742971 | 0.306066 |
| 832 | Ivory Coast | 2014 | 3.570369 | 8.333736 | 0.710992 | 47.400002 | 0.780773 | -0.080097 | 0.671356 | 0.647041 | 0.290651 |
| 833 | Ivory Coast | 2015 | 4.445039 | 8.393250 | 0.703992 | 47.700001 | 0.799746 | -0.053405 | 0.744250 | 0.663882 | 0.347229 |
| 834 | Ivory Coast | 2016 | 4.542546 | 8.437222 | 0.617401 | 48.299999 | 0.768789 | -0.042712 | 0.757453 | 0.703617 | 0.378029 |
| 835 | Ivory Coast | 2017 | 5.037735 | 8.482758 | 0.661375 | 48.900002 | 0.732098 | -0.110538 | 0.770940 | 0.697735 | 0.357456 |
| 836 | Ivory Coast | 2018 | 5.268375 | 8.522961 | 0.620883 | 49.500000 | 0.712590 | -0.050007 | 0.790967 | 0.682098 | 0.385631 |
| 837 | Ivory Coast | 2019 | 5.392012 | 8.563745 | 0.679386 | 50.099998 | 0.735712 | -0.017261 | 0.799271 | 0.674235 | 0.425407 |
| 838 | Ivory Coast | 2020 | 5.256504 | 8.564923 | 0.613106 | 50.700001 | 0.769998 | 0.015564 | 0.776687 | 0.692647 | 0.339919 |
| 839 | Jamaica | 2006 | 6.207882 | 9.225333 | 0.909084 | 64.900002 | 0.738236 | -0.003836 | 0.945988 | 0.788478 | 0.200847 |
| 840 | Jamaica | 2011 | 5.374446 | 9.163817 | 0.854584 | 66.220001 | 0.795614 | -0.063646 | 0.909116 | 0.835872 | 0.237159 |
| 841 | Jamaica | 2013 | 5.708887 | 9.151133 | 0.864943 | 66.459999 | 0.793195 | -0.020864 | 0.930722 | 0.733613 | 0.312485 |
| 842 | Jamaica | 2014 | 5.310539 | 9.152293 | 0.874232 | 66.580002 | 0.808973 | -0.000519 | 0.861133 | 0.737161 | 0.309985 |
| 843 | Jamaica | 2017 | 5.889759 | 9.169349 | 0.913030 | 67.099998 | 0.860676 | -0.129574 | 0.882796 | 0.769282 | 0.243400 |
| 844 | Jamaica | 2019 | 6.309239 | 9.186201 | 0.877814 | 67.500000 | 0.890671 | -0.136797 | 0.885330 | 0.752041 | 0.195284 |
| 845 | Japan | 2005 | 6.515817 | 10.529193 | 0.927712 | 73.199997 | 0.867779 | NaN | 0.698930 | 0.738980 | 0.153151 |
| 846 | Japan | 2007 | 6.238198 | 10.557917 | 0.938148 | 73.440002 | 0.796054 | -0.090048 | 0.809233 | 0.731494 | 0.206580 |
| 847 | Japan | 2008 | 5.910679 | 10.546437 | 0.887304 | 73.559998 | 0.772070 | -0.135062 | 0.816475 | 0.779842 | 0.190774 |
| 848 | Japan | 2009 | 5.844999 | 10.490875 | 0.888357 | 73.680000 | 0.729888 | -0.209903 | 0.740108 | 0.784990 | 0.169478 |
| 849 | Japan | 2010 | 6.056753 | 10.531758 | 0.901925 | 73.800003 | 0.771722 | -0.140231 | 0.769557 | 0.827118 | 0.187703 |
| 850 | Japan | 2011 | 6.262794 | 10.532456 | 0.916704 | 73.980003 | 0.814396 | -0.051788 | 0.733799 | 0.775717 | 0.181055 |
| 851 | Japan | 2012 | 5.968216 | 10.548893 | 0.905295 | 74.160004 | 0.752832 | NaN | 0.692387 | 0.776911 | 0.171475 |
| 852 | Japan | 2013 | 5.959362 | 10.570142 | 0.923688 | 74.339996 | 0.821417 | -0.146817 | 0.650498 | 0.793809 | 0.174622 |
| 853 | Japan | 2014 | 5.922621 | 10.575209 | 0.900040 | 74.519997 | 0.838052 | -0.139266 | 0.617483 | 0.741508 | 0.189433 |
| 854 | Japan | 2015 | 5.879684 | 10.588425 | 0.922657 | 74.699997 | 0.831694 | -0.155128 | 0.654443 | 0.768091 | 0.176409 |
| 855 | Japan | 2016 | 5.954651 | 10.594784 | 0.899774 | 74.800003 | 0.836065 | -0.062039 | 0.697639 | 0.760109 | 0.192403 |
| 856 | Japan | 2017 | 5.910676 | 10.617880 | 0.881961 | 74.900002 | 0.849397 | -0.205958 | 0.659199 | 0.740388 | 0.175512 |
| 857 | Japan | 2018 | 5.793575 | 10.623133 | 0.886432 | 75.000000 | 0.773472 | -0.261265 | 0.686785 | 0.703355 | 0.185300 |
| 858 | Japan | 2019 | 5.908039 | 10.631743 | 0.877651 | 75.099998 | 0.806472 | -0.254619 | 0.617188 | 0.742844 | 0.194410 |
| 859 | Japan | 2020 | 6.117963 | 10.579548 | 0.887249 | 75.199997 | 0.806036 | -0.258745 | 0.608699 | 0.742469 | 0.186461 |
| 860 | Jordan | 2005 | 6.294660 | 9.245755 | 0.920013 | 63.500000 | NaN | NaN | 0.669727 | 0.695953 | 0.239560 |
| 861 | Jordan | 2007 | 5.598057 | 9.320656 | 0.840607 | 63.980000 | 0.646079 | -0.111973 | 0.663645 | 0.682662 | 0.239750 |
| 862 | Jordan | 2008 | 4.930058 | 9.343456 | 0.766224 | 64.220001 | NaN | -0.127316 | 0.709403 | 0.668975 | 0.331201 |
| 863 | Jordan | 2009 | 5.999859 | 9.346684 | 0.899034 | 64.459999 | 0.770954 | -0.075281 | 0.739464 | 0.644645 | 0.264641 |
| 864 | Jordan | 2010 | 5.569942 | 9.317488 | 0.917989 | 64.699997 | 0.788073 | -0.046459 | NaN | 0.643089 | 0.343419 |
| 865 | Jordan | 2011 | 5.539328 | 9.289198 | 0.877919 | 65.000000 | 0.759565 | -0.142816 | NaN | 0.612024 | 0.260324 |
| 866 | Jordan | 2012 | 5.131996 | 9.261048 | 0.829496 | 65.300003 | 0.693142 | -0.160105 | NaN | 0.564725 | 0.345336 |
| 867 | Jordan | 2013 | 5.171953 | 9.237214 | 0.840379 | 65.599998 | 0.692227 | -0.116707 | NaN | 0.684084 | 0.286033 |
| 868 | Jordan | 2014 | 5.333022 | 9.221872 | 0.816131 | 65.900002 | 0.728743 | -0.104096 | NaN | 0.660056 | 0.312646 |
| 869 | Jordan | 2015 | 5.404593 | 9.207395 | 0.830444 | 66.199997 | 0.766517 | -0.045793 | NaN | 0.689984 | 0.305196 |
| 870 | Jordan | 2016 | 5.271285 | 9.196954 | 0.819945 | 66.400002 | 0.771351 | -0.038175 | NaN | 0.640658 | 0.311913 |
| 871 | Jordan | 2017 | 4.808083 | 9.194330 | 0.814665 | 66.599998 | 0.766262 | -0.152088 | NaN | 0.627798 | 0.391505 |
| 872 | Jordan | 2018 | 4.638934 | 9.195625 | 0.799544 | 66.800003 | 0.762420 | -0.185849 | NaN | NaN | NaN |
| 873 | Jordan | 2019 | 4.452548 | 9.200901 | 0.792560 | 67.000000 | 0.725756 | -0.164765 | NaN | NaN | NaN |
| 874 | Jordan | 2020 | 4.093992 | 9.149995 | 0.708840 | 67.199997 | 0.778533 | -0.149826 | NaN | NaN | NaN |
| 875 | Kazakhstan | 2006 | 5.475948 | 9.804373 | 0.872089 | 58.200001 | 0.730546 | -0.274000 | 0.864982 | 0.668788 | 0.185065 |
| 876 | Kazakhstan | 2007 | 5.718554 | 9.878194 | 0.860893 | 58.700001 | 0.806300 | -0.245569 | 0.865183 | 0.651071 | 0.178508 |
| 877 | Kazakhstan | 2008 | 5.886420 | 9.898478 | 0.839467 | 59.200001 | 0.726584 | -0.220827 | 0.899164 | 0.675005 | 0.159726 |
| 878 | Kazakhstan | 2009 | 5.382563 | 9.884036 | 0.892998 | 59.700001 | 0.856448 | -0.249477 | 0.844568 | 0.678526 | 0.128600 |
| 879 | Kazakhstan | 2010 | 5.514287 | 9.940362 | 0.903786 | 60.200001 | 0.784852 | -0.215105 | 0.822704 | 0.691867 | 0.148951 |
| 880 | Kazakhstan | 2011 | 5.735663 | 9.997437 | 0.904971 | 60.720001 | 0.877888 | -0.235396 | 0.801724 | 0.695144 | 0.154434 |
| 881 | Kazakhstan | 2012 | 5.759470 | 10.030233 | 0.891717 | 61.240002 | 0.839832 | -0.171062 | 0.876682 | 0.739843 | 0.184381 |
| 882 | Kazakhstan | 2013 | 5.835483 | 10.074108 | 0.889010 | 61.759998 | 0.781591 | -0.229209 | 0.819989 | 0.673899 | 0.164444 |
| 883 | Kazakhstan | 2014 | 5.970098 | 10.100524 | 0.795293 | 62.279999 | 0.799463 | 0.004009 | 0.805351 | 0.717840 | 0.169457 |
| 884 | Kazakhstan | 2015 | 5.949995 | 10.097837 | 0.931349 | 62.799999 | 0.740133 | -0.036993 | 0.713844 | 0.730147 | 0.173994 |
| 885 | Kazakhstan | 2016 | 5.533552 | 10.094557 | 0.927811 | 63.400002 | 0.782806 | -0.036056 | 0.702017 | 0.702479 | 0.155415 |
| 886 | Kazakhstan | 2017 | 5.882351 | 10.121135 | 0.914093 | 64.000000 | 0.745244 | -0.034828 | 0.755251 | 0.756762 | 0.171486 |
| 887 | Kazakhstan | 2018 | 6.007636 | 10.148169 | 0.936657 | 64.599998 | 0.840183 | -0.098020 | 0.823783 | 0.693199 | 0.161542 |
| 888 | Kazakhstan | 2019 | 6.272268 | 10.179278 | 0.951050 | 65.199997 | 0.852387 | -0.055017 | 0.708279 | 0.787135 | 0.139133 |
| 889 | Kazakhstan | 2020 | 6.168269 | 10.135336 | 0.966449 | 65.800003 | 0.872100 | -0.056175 | 0.660799 | 0.684103 | 0.150360 |
| 890 | Kenya | 2006 | 4.223234 | 8.038949 | 0.908798 | 50.220001 | 0.615886 | -0.020096 | 0.860257 | 0.705087 | 0.198192 |
| 891 | Kenya | 2007 | 4.575658 | 8.077526 | 0.841112 | 51.540001 | 0.749842 | 0.053689 | 0.798739 | 0.725196 | 0.161941 |
| 892 | Kenya | 2008 | 4.015275 | 8.052174 | 0.826555 | 52.860001 | 0.620296 | -0.011607 | 0.909447 | 0.772227 | 0.148997 |
| 893 | Kenya | 2009 | 4.270435 | 8.057199 | 0.789220 | 54.180000 | 0.583595 | 0.099646 | 0.912947 | 0.771880 | 0.182592 |
| 894 | Kenya | 2010 | 4.255859 | 8.110683 | 0.805326 | 55.500000 | 0.635457 | 0.018628 | 0.917921 | 0.819122 | 0.123202 |
| 895 | Kenya | 2011 | 4.405310 | 8.143036 | 0.846308 | 56.060001 | 0.708659 | 0.021800 | 0.922664 | 0.760372 | 0.227972 |
| 896 | Kenya | 2012 | 4.547335 | 8.161031 | 0.831410 | 56.619999 | 0.627654 | 0.065733 | 0.911273 | 0.706964 | 0.194177 |
| 897 | Kenya | 2013 | 3.795383 | 8.191969 | 0.824806 | 57.180000 | 0.708332 | 0.212380 | 0.861003 | 0.765043 | 0.161331 |
| 898 | Kenya | 2014 | 4.904580 | 8.218560 | 0.765436 | 57.740002 | 0.819019 | 0.172233 | 0.849194 | 0.814436 | 0.221097 |
| 899 | Kenya | 2015 | 4.357618 | 8.249250 | 0.776923 | 58.299999 | 0.792990 | 0.220653 | 0.852550 | 0.702257 | 0.172422 |
| 900 | Kenya | 2016 | 4.396128 | 8.282166 | 0.705922 | 58.900002 | 0.748508 | 0.298327 | 0.828412 | 0.742762 | 0.225648 |
| 901 | Kenya | 2017 | 4.475654 | 8.305535 | 0.714604 | 59.500000 | 0.853394 | 0.234422 | 0.854000 | 0.788452 | 0.230210 |
| 902 | Kenya | 2018 | 4.655703 | 8.343744 | 0.706720 | 60.099998 | 0.821413 | 0.291247 | 0.844244 | 0.759103 | 0.236921 |
| 903 | Kenya | 2019 | 4.618850 | 8.373293 | 0.675932 | 60.700001 | 0.817757 | 0.310065 | 0.794370 | 0.751439 | 0.250687 |
| 904 | Kenya | 2020 | 4.546584 | 8.365282 | 0.673718 | 61.299999 | 0.702034 | 0.259970 | 0.836516 | 0.733435 | 0.296980 |
| 905 | Kosovo | 2007 | 5.103906 | 8.927753 | 0.847812 | NaN | 0.381364 | 0.143901 | 0.894462 | 0.654866 | 0.236699 |
| 906 | Kosovo | 2008 | 5.521660 | 8.980872 | 0.883843 | NaN | NaN | 0.090464 | 0.849059 | NaN | 0.317828 |
| 907 | Kosovo | 2009 | 5.891433 | 9.008162 | 0.830427 | NaN | 0.506415 | 0.200504 | 0.967839 | 0.597583 | 0.168830 |
| 908 | Kosovo | 2010 | 5.176601 | 9.032693 | 0.707959 | NaN | 0.451444 | 0.169696 | 0.967272 | 0.695178 | 0.117717 |
| 909 | Kosovo | 2011 | 4.859502 | 9.066925 | 0.759102 | NaN | 0.588979 | 0.003699 | 0.919212 | 0.695966 | 0.124438 |
| 910 | Kosovo | 2012 | 5.639588 | 9.085688 | 0.757147 | NaN | 0.635793 | 0.027182 | 0.949651 | 0.595572 | 0.099630 |
| 911 | Kosovo | 2013 | 6.125758 | 9.113430 | 0.720750 | NaN | 0.568463 | 0.114904 | 0.935095 | 0.691511 | 0.202731 |
| 912 | Kosovo | 2014 | 5.000375 | 9.128522 | 0.705632 | NaN | 0.441391 | 0.012095 | 0.775201 | 0.636128 | 0.205950 |
| 913 | Kosovo | 2015 | 5.077461 | 9.182307 | 0.805271 | NaN | 0.561048 | 0.180851 | 0.850647 | 0.753090 | 0.179989 |
| 914 | Kosovo | 2016 | 5.759412 | 9.228177 | 0.823803 | NaN | 0.827399 | 0.124869 | 0.940898 | 0.703887 | 0.149607 |
| 915 | Kosovo | 2017 | 6.149200 | 9.262030 | 0.792087 | NaN | 0.857677 | 0.117175 | 0.925192 | 0.738436 | 0.185879 |
| 916 | Kosovo | 2018 | 6.391826 | 9.296085 | 0.822407 | NaN | 0.889737 | 0.268795 | 0.922078 | 0.778271 | 0.170248 |
| 917 | Kosovo | 2019 | 6.425144 | 9.338535 | 0.842511 | NaN | 0.841190 | 0.246990 | 0.920297 | 0.748522 | 0.140792 |
| 918 | Kosovo | 2020 | 6.294414 | NaN | 0.792374 | NaN | 0.879838 | NaN | 0.909894 | 0.726240 | 0.201458 |
| 919 | Kuwait | 2006 | 6.075547 | 11.228230 | 0.918950 | 63.959999 | 0.769072 | -0.235777 | 0.328158 | 0.845954 | 0.182275 |
| 920 | Kuwait | 2009 | 6.585246 | 11.064857 | 0.926412 | 64.440002 | 0.818781 | 0.006779 | 0.675122 | 0.718377 | 0.251760 |
| 921 | Kuwait | 2010 | 6.798151 | 10.982072 | 0.892722 | 64.599998 | 0.703020 | -0.031405 | 0.486111 | 0.717980 | 0.203396 |
| 922 | Kuwait | 2011 | 6.377699 | 11.016783 | 0.881912 | 64.900002 | 0.768604 | NaN | 0.560424 | 0.793242 | 0.176825 |
| 923 | Kuwait | 2012 | 6.221095 | 11.025439 | 0.888917 | 65.199997 | 0.934050 | NaN | NaN | 0.820709 | 0.095490 |
| 924 | Kuwait | 2013 | 6.480031 | 10.985214 | 0.861948 | 65.500000 | 0.750525 | NaN | NaN | 0.752348 | 0.282629 |
| 925 | Kuwait | 2014 | 6.180139 | 10.944600 | NaN | 65.800003 | NaN | NaN | NaN | NaN | NaN |
| 926 | Kuwait | 2015 | 6.146032 | 10.912070 | 0.823018 | 66.099998 | 0.821662 | 0.081595 | NaN | 0.722894 | 0.323691 |
| 927 | Kuwait | 2016 | 5.947195 | 10.909778 | 0.845222 | 66.300003 | 0.840967 | -0.075156 | NaN | 0.688287 | 0.314923 |
| 928 | Kuwait | 2017 | 6.093905 | 10.836743 | 0.853491 | 66.500000 | 0.884182 | -0.004677 | NaN | 0.692072 | 0.307321 |
| 929 | Kuwait | 2019 | 6.106120 | 10.816696 | 0.841520 | 66.900002 | 0.867274 | -0.104161 | NaN | 0.695363 | 0.302876 |
| 930 | Kyrgyzstan | 2006 | 4.641399 | 8.185375 | 0.844137 | 59.980000 | 0.677572 | -0.140118 | 0.878633 | 0.654618 | 0.159483 |
| 931 | Kyrgyzstan | 2007 | 4.697762 | 8.257814 | 0.833098 | 60.259998 | 0.683523 | -0.091322 | 0.929055 | 0.655074 | 0.129503 |
| 932 | Kyrgyzstan | 2008 | 4.736588 | 8.328985 | 0.792133 | 60.540001 | 0.719029 | -0.099744 | 0.922627 | 0.623046 | 0.146872 |
| 933 | Kyrgyzstan | 2009 | 5.069054 | 8.345366 | 0.854936 | 60.820000 | 0.698920 | -0.139841 | 0.896227 | 0.607278 | 0.164817 |
| 934 | Kyrgyzstan | 2010 | 4.996411 | 8.328712 | 0.885363 | 61.099998 | 0.720051 | -0.071627 | 0.925794 | 0.649522 | 0.123463 |
| 935 | Kyrgyzstan | 2011 | 4.921049 | 8.374398 | 0.891404 | 61.520000 | 0.747808 | -0.154570 | 0.932497 | 0.681429 | 0.151316 |
| 936 | Kyrgyzstan | 2012 | 5.207786 | 8.356864 | 0.856182 | 61.939999 | 0.702732 | -0.078886 | 0.892037 | 0.690524 | 0.182383 |
| 937 | Kyrgyzstan | 2013 | 5.402427 | 8.440616 | 0.850716 | 62.360001 | 0.755037 | -0.085081 | 0.899560 | 0.722004 | 0.134911 |
| 938 | Kyrgyzstan | 2014 | 5.252193 | 8.460006 | 0.898025 | 62.779999 | 0.736290 | 0.355367 | 0.896767 | 0.725461 | 0.185025 |
| 939 | Kyrgyzstan | 2015 | 4.905376 | 8.477442 | 0.856585 | 63.200001 | 0.813176 | 0.199768 | 0.857725 | 0.766794 | 0.173476 |
| 940 | Kyrgyzstan | 2016 | 4.856534 | 8.499515 | 0.914375 | 63.500000 | 0.813939 | 0.056209 | 0.916923 | 0.778171 | 0.126100 |
| 941 | Kyrgyzstan | 2017 | 5.629537 | 8.526488 | 0.882587 | 63.799999 | 0.859390 | 0.143024 | 0.874494 | 0.755125 | 0.160438 |
| 942 | Kyrgyzstan | 2018 | 5.297383 | 8.543475 | 0.898148 | 64.099998 | 0.944948 | 0.266904 | 0.907405 | 0.763271 | 0.203300 |
| 943 | Kyrgyzstan | 2019 | 5.685221 | 8.566573 | 0.877028 | 64.400002 | 0.920436 | -0.002361 | 0.884540 | 0.765742 | 0.207229 |
| 944 | Kyrgyzstan | 2020 | 6.249586 | 8.503411 | 0.902223 | 64.699997 | 0.934885 | 0.102866 | 0.931318 | 0.803025 | 0.257813 |
| 945 | Laos | 2006 | 5.076226 | 8.250724 | 0.806987 | 53.919998 | 0.925082 | 0.439215 | 0.687814 | 0.885816 | 0.162685 |
| 946 | Laos | 2007 | 5.363855 | 8.307173 | 0.789621 | 54.439999 | 0.866525 | 0.478057 | 0.580067 | 0.861139 | 0.135671 |
| 947 | Laos | 2008 | 5.044099 | 8.365554 | 0.807086 | 54.959999 | 0.886214 | 0.416207 | 0.637409 | 0.829270 | 0.201755 |
| 948 | Laos | 2011 | 4.703750 | 8.548466 | 0.690878 | 56.299999 | 0.881634 | 0.458593 | 0.587322 | 0.899812 | 0.225278 |
| 949 | Laos | 2012 | 4.876085 | 8.610508 | 0.692628 | 56.599998 | NaN | 0.232109 | NaN | 0.916801 | 0.386679 |
| 950 | Laos | 2017 | 4.623141 | 8.889833 | 0.707336 | 58.299999 | 0.891001 | 0.073113 | 0.591617 | 0.872792 | 0.344226 |
| 951 | Laos | 2018 | 4.859402 | 8.934958 | 0.704738 | 58.700001 | 0.906661 | 0.141146 | 0.634240 | 0.852214 | 0.331883 |
| 952 | Laos | 2019 | 5.196856 | 8.965257 | 0.729444 | 59.099998 | 0.906153 | 0.061082 | 0.620234 | 0.878180 | 0.306144 |
| 953 | Laos | 2020 | 5.284391 | 8.959955 | 0.660396 | 59.500000 | 0.915028 | 0.141431 | 0.747998 | 0.821680 | 0.358349 |
| 954 | Latvia | 2006 | 4.709502 | 10.032048 | 0.884499 | 63.160000 | 0.640807 | -0.229206 | 0.937049 | 0.654296 | 0.234135 |
| 955 | Latvia | 2007 | 4.666972 | 10.135619 | 0.835509 | 63.520000 | 0.700174 | -0.166734 | 0.923953 | 0.672521 | 0.246863 |
| 956 | Latvia | 2008 | 5.145375 | 10.112092 | 0.855418 | 63.880001 | 0.630111 | -0.203171 | 0.926328 | 0.638644 | 0.214901 |
| 957 | Latvia | 2009 | 4.668911 | 9.975006 | 0.806939 | 64.239998 | 0.437065 | -0.180326 | 0.942090 | 0.525005 | 0.242197 |
| 958 | Latvia | 2011 | 4.966812 | 10.029216 | 0.836042 | 64.860001 | 0.564464 | -0.002395 | 0.934256 | 0.563278 | 0.221713 |
| 959 | Latvia | 2012 | 5.125025 | 10.082130 | 0.851195 | 65.120003 | 0.563812 | -0.037763 | 0.894979 | 0.560013 | 0.232225 |
| 960 | Latvia | 2013 | 5.069770 | 10.115854 | 0.834023 | 65.379997 | 0.630508 | -0.072923 | 0.836554 | 0.642102 | 0.227449 |
| 961 | Latvia | 2014 | 5.729115 | 10.144242 | 0.881256 | 65.639999 | 0.670653 | -0.043007 | 0.803688 | 0.652273 | 0.225979 |
| 962 | Latvia | 2015 | 5.880598 | 10.184513 | 0.879372 | 65.900002 | 0.656393 | -0.077392 | 0.808400 | 0.608380 | 0.228137 |
| 963 | Latvia | 2016 | 5.940446 | 10.211235 | 0.917074 | 66.199997 | 0.685299 | -0.156372 | 0.867640 | 0.653751 | 0.231384 |
| 964 | Latvia | 2017 | 5.977818 | 10.257271 | 0.895099 | 66.500000 | 0.699520 | -0.154460 | 0.798378 | 0.623313 | 0.231753 |
| 965 | Latvia | 2018 | 5.901154 | 10.307017 | 0.913276 | 66.800003 | 0.608208 | -0.212329 | 0.798949 | 0.585233 | 0.191871 |
| 966 | Latvia | 2019 | 5.969754 | 10.336246 | 0.935501 | 67.099998 | 0.697935 | -0.193979 | 0.789227 | 0.575235 | 0.211631 |
| 967 | Latvia | 2020 | 6.229009 | 10.299590 | 0.928012 | 67.400002 | 0.820112 | -0.077660 | 0.808822 | 0.713628 | 0.201582 |
| 968 | Lebanon | 2005 | 5.491245 | 9.565474 | 0.796278 | 64.599998 | 0.703206 | NaN | 0.945177 | 0.584244 | 0.292150 |
| 969 | Lebanon | 2006 | 4.653104 | 9.567953 | 0.853151 | 64.720001 | 0.670194 | 0.069380 | 0.901960 | 0.548371 | 0.319716 |
| 970 | Lebanon | 2008 | 4.594851 | 9.742742 | 0.717357 | 64.959999 | 0.524063 | 0.034625 | 0.926726 | 0.526726 | 0.365418 |
| 971 | Lebanon | 2009 | 5.205999 | 9.830077 | 0.736412 | 65.080002 | 0.664734 | 0.070730 | 0.937025 | 0.527855 | 0.401289 |
| 972 | Lebanon | 2010 | 5.031899 | 9.878128 | 0.721425 | 65.199997 | 0.677639 | 0.072939 | 0.949063 | 0.525078 | 0.341206 |
| 973 | Lebanon | 2011 | 5.187572 | 9.837661 | 0.732915 | 65.279999 | 0.657106 | 0.005815 | 0.910561 | 0.578011 | 0.320167 |
| 974 | Lebanon | 2012 | 4.572567 | 9.800110 | 0.712611 | 65.360001 | 0.620627 | -0.005738 | 0.855778 | 0.499441 | 0.338857 |
| 975 | Lebanon | 2013 | 4.983289 | 9.771832 | 0.708228 | 65.440002 | 0.654868 | -0.003850 | 0.920828 | 0.498864 | 0.409337 |
| 976 | Lebanon | 2014 | 5.233026 | 9.739010 | 0.758719 | 65.519997 | 0.657208 | -0.012232 | 0.939358 | 0.558848 | 0.267213 |
| 977 | Lebanon | 2015 | 5.171971 | 9.698873 | 0.741708 | 65.599998 | 0.596750 | 0.072652 | 0.888953 | 0.567873 | 0.242554 |
| 978 | Lebanon | 2016 | 5.270724 | 9.687102 | 0.827886 | 66.099998 | 0.657357 | 0.031364 | 0.853114 | 0.552651 | 0.263446 |
| 979 | Lebanon | 2017 | 5.153990 | 9.680673 | 0.776583 | 66.599998 | 0.604554 | -0.074190 | 0.910727 | 0.515444 | 0.243549 |
| 980 | Lebanon | 2018 | 5.167187 | 9.655796 | 0.829381 | 67.099998 | 0.607031 | -0.065524 | 0.906650 | 0.463881 | 0.270689 |
| 981 | Lebanon | 2019 | 4.024220 | 9.596783 | 0.865969 | 67.599998 | 0.447001 | -0.081082 | 0.890416 | 0.321690 | 0.494499 |
| 982 | Lesotho | 2011 | 4.897515 | 7.777329 | 0.824085 | 45.740002 | 0.618260 | -0.086918 | 0.767676 | 0.793473 | 0.170010 |
| 983 | Lesotho | 2016 | 3.808205 | 7.952509 | 0.798059 | 46.599998 | 0.729490 | -0.098773 | 0.742873 | 0.732466 | 0.270283 |
| 984 | Lesotho | 2017 | 3.795301 | 7.931326 | 0.768552 | 47.299999 | 0.756505 | -0.144852 | 0.796859 | 0.746202 | 0.255303 |
| 985 | Lesotho | 2019 | 3.511781 | 7.925777 | 0.789705 | 48.700001 | 0.716314 | -0.130536 | 0.914951 | 0.734880 | 0.273426 |
| 986 | Liberia | 2007 | 3.701401 | 7.195504 | 0.593732 | 49.139999 | 0.790374 | 0.115221 | 0.775735 | 0.612697 | 0.435410 |
| 987 | Liberia | 2008 | 4.221354 | 7.223229 | 0.618693 | 49.959999 | 0.724083 | -0.034547 | 0.839668 | 0.585067 | 0.261133 |
| 988 | Liberia | 2010 | 4.196063 | 7.258445 | 0.827099 | 51.599998 | 0.819005 | -0.038288 | 0.818430 | 0.595008 | 0.216883 |
| 989 | Liberia | 2014 | 4.571419 | 7.391012 | 0.708302 | 53.279999 | 0.590451 | -0.029854 | 0.868966 | 0.542849 | 0.442860 |
| 990 | Liberia | 2015 | 2.701591 | 7.365483 | 0.637666 | 53.700001 | 0.671431 | -0.061490 | 0.902673 | 0.505067 | 0.388489 |
| 991 | Liberia | 2016 | 3.354676 | 7.324065 | 0.642615 | 54.500000 | 0.763476 | 0.033054 | 0.901267 | 0.635528 | 0.509047 |
| 992 | Liberia | 2017 | 4.424491 | 7.323595 | 0.684867 | 55.299999 | 0.733390 | -0.012056 | 0.866806 | 0.667946 | 0.391331 |
| 993 | Liberia | 2018 | 4.134853 | 7.311222 | 0.726750 | 56.099998 | 0.765770 | 0.049856 | 0.867924 | 0.659732 | 0.436099 |
| 994 | Liberia | 2019 | 5.121461 | 7.263904 | 0.712474 | 56.900002 | 0.705875 | 0.050612 | 0.828469 | 0.635609 | 0.389133 |
| 995 | Libya | 2012 | 5.754394 | 9.841973 | 0.854931 | 62.660000 | 0.711519 | -0.031701 | 0.790556 | 0.694884 | 0.316150 |
| 996 | Libya | 2015 | 5.615405 | 9.307688 | 0.867988 | 62.299999 | 0.774545 | -0.044114 | NaN | 0.703950 | 0.368905 |
| 997 | Libya | 2016 | 5.433583 | 9.267895 | 0.876066 | 62.299999 | 0.822385 | -0.089468 | NaN | 0.717785 | 0.383074 |
| 998 | Libya | 2017 | 5.646852 | 9.490847 | 0.822759 | 62.299999 | 0.778696 | -0.019349 | 0.673066 | 0.697049 | 0.379374 |
| 999 | Libya | 2018 | 5.493978 | 9.617004 | 0.824165 | 62.299999 | 0.780559 | -0.101244 | 0.645839 | 0.705535 | 0.398903 |
| 1000 | Libya | 2019 | 5.330222 | 9.627350 | 0.826719 | 62.299999 | 0.761964 | -0.072673 | 0.686413 | 0.708741 | 0.400737 |
| 1001 | Lithuania | 2006 | 5.954443 | 10.045794 | 0.930440 | 63.139999 | 0.567255 | -0.295096 | 0.966879 | 0.621323 | 0.253998 |
| 1002 | Lithuania | 2007 | 5.808285 | 10.162817 | 0.940792 | 63.480000 | 0.589662 | -0.281804 | 0.966326 | 0.589249 | 0.279184 |
| 1003 | Lithuania | 2008 | 5.553926 | 10.199043 | 0.913667 | 63.820000 | 0.621060 | -0.259447 | 0.960843 | 0.532837 | 0.275796 |
| 1004 | Lithuania | 2009 | 5.466921 | 10.049811 | 0.932609 | 64.160004 | 0.495956 | -0.303204 | 0.978800 | 0.526198 | 0.270838 |
| 1005 | Lithuania | 2010 | 5.065825 | 10.085495 | 0.881811 | 64.500000 | 0.519352 | -0.274880 | 0.962167 | 0.473150 | 0.272029 |
| 1006 | Lithuania | 2011 | 5.432437 | 10.166590 | 0.911411 | 64.699997 | 0.565797 | -0.147912 | 0.963512 | 0.569533 | 0.274637 |
| 1007 | Lithuania | 2012 | 5.771037 | 10.217619 | 0.918690 | 64.900002 | 0.503027 | -0.273212 | 0.956959 | 0.580971 | 0.277386 |
| 1008 | Lithuania | 2013 | 5.595689 | 10.262704 | 0.912514 | 65.099998 | 0.555815 | -0.236610 | 0.936336 | 0.580804 | 0.293729 |
| 1009 | Lithuania | 2014 | 6.125724 | 10.305781 | 0.908240 | 65.300003 | 0.507947 | -0.263435 | 0.956348 | 0.619343 | 0.286911 |
| 1010 | Lithuania | 2015 | 5.711378 | 10.335316 | 0.928524 | 65.500000 | 0.641470 | -0.253632 | 0.924174 | 0.594610 | 0.276452 |
| 1011 | Lithuania | 2016 | 5.865552 | 10.373261 | 0.937873 | 66.099998 | 0.614239 | -0.266326 | 0.949393 | 0.594167 | 0.249856 |
| 1012 | Lithuania | 2017 | 6.272941 | 10.428843 | 0.926317 | 66.699997 | 0.749307 | -0.173561 | 0.789710 | 0.607613 | 0.195119 |
| 1013 | Lithuania | 2018 | 6.308879 | 10.474184 | 0.929350 | 67.300003 | 0.698945 | -0.236668 | 0.851745 | 0.516805 | 0.213560 |
| 1014 | Lithuania | 2019 | 6.064098 | 10.517996 | 0.917578 | 67.900002 | 0.780266 | -0.251475 | 0.782501 | 0.566024 | 0.276054 |
| 1015 | Lithuania | 2020 | 6.391379 | 10.503607 | 0.952544 | 68.500000 | 0.824061 | -0.121781 | 0.829205 | 0.660230 | 0.201912 |
| 1016 | Luxembourg | 2009 | 6.957920 | 11.562458 | 0.938559 | 71.440002 | 0.939102 | 0.126973 | 0.431607 | 0.799493 | 0.238022 |
| 1017 | Luxembourg | 2010 | 7.097252 | 11.591707 | 0.952372 | 71.699997 | 0.908303 | 0.095851 | 0.423341 | 0.808783 | 0.216064 |
| 1018 | Luxembourg | 2011 | 7.101400 | 11.594556 | 0.934091 | 71.879997 | 0.961831 | 0.105871 | 0.388171 | 0.836459 | 0.200137 |
| 1019 | Luxembourg | 2012 | 6.964097 | 11.567009 | 0.913908 | 72.059998 | 0.916521 | 0.058670 | 0.402753 | 0.815249 | 0.227412 |
| 1020 | Luxembourg | 2013 | 7.130809 | 11.579789 | 0.916683 | 72.239998 | 0.789655 | -0.054244 | 0.300812 | 0.640380 | 0.184800 |
| 1021 | Luxembourg | 2014 | 6.891127 | 11.598289 | 0.875469 | 72.419998 | 0.937988 | 0.105852 | 0.366287 | 0.803084 | 0.170409 |
| 1022 | Luxembourg | 2015 | 6.701571 | 11.616853 | 0.933605 | 72.599998 | 0.932256 | 0.052100 | 0.375390 | 0.757445 | 0.193050 |
| 1023 | Luxembourg | 2016 | 6.967341 | 11.640030 | 0.941261 | 72.599998 | 0.882365 | 0.018698 | 0.356336 | 0.757950 | 0.192301 |
| 1024 | Luxembourg | 2017 | 7.061381 | 11.633572 | 0.905436 | 72.599998 | 0.902822 | 0.044103 | 0.330174 | 0.765817 | 0.184467 |
| 1025 | Luxembourg | 2018 | 7.242631 | 11.644917 | 0.902192 | 72.599998 | 0.883930 | -0.021763 | 0.385146 | 0.750309 | 0.201894 |
| 1026 | Luxembourg | 2019 | 7.404016 | 11.648169 | 0.912105 | 72.599998 | 0.930321 | -0.045058 | 0.389598 | 0.789186 | 0.211640 |
| 1027 | Madagascar | 2006 | 3.979751 | 7.375728 | 0.711135 | 54.040001 | NaN | -0.038620 | NaN | 0.701799 | 0.161333 |
| 1028 | Madagascar | 2008 | 4.640079 | 7.438793 | 0.775689 | 54.919998 | 0.332436 | -0.099392 | 0.773067 | 0.614425 | 0.214525 |
| 1029 | Madagascar | 2011 | 4.381415 | 7.336246 | 0.818403 | 56.220001 | 0.545556 | -0.062000 | 0.897100 | 0.509871 | 0.234826 |
| 1030 | Madagascar | 2012 | 3.550610 | 7.338574 | 0.673088 | 56.639999 | 0.487008 | -0.054980 | 0.853590 | 0.689856 | 0.193977 |
| 1031 | Madagascar | 2013 | 3.815607 | 7.334185 | 0.672547 | 57.060001 | 0.479550 | -0.018502 | 0.867708 | 0.734316 | 0.241231 |
| 1032 | Madagascar | 2014 | 3.675627 | 7.340022 | 0.655214 | 57.480000 | 0.528805 | -0.023182 | 0.791056 | 0.747616 | 0.192182 |
| 1033 | Madagascar | 2015 | 3.592514 | 7.343922 | 0.646717 | 57.900002 | 0.544754 | -0.040822 | 0.860953 | 0.801759 | 0.226243 |
| 1034 | Madagascar | 2016 | 3.663086 | 7.356195 | 0.746497 | 58.299999 | 0.569645 | -0.068980 | 0.864171 | 0.813191 | 0.204255 |
| 1035 | Madagascar | 2017 | 4.078620 | 7.367975 | 0.626332 | 58.700001 | 0.570348 | -0.033295 | 0.847261 | 0.751698 | 0.374838 |
| 1036 | Madagascar | 2018 | 4.070587 | 7.385916 | 0.665513 | 59.099998 | 0.551473 | 0.002596 | 0.889146 | 0.752341 | 0.362014 |
| 1037 | Madagascar | 2019 | 4.339087 | 7.406237 | 0.700610 | 59.500000 | 0.549535 | -0.012469 | 0.719983 | 0.723195 | 0.303960 |
| 1038 | Malawi | 2006 | 3.829868 | 6.678227 | 0.553879 | 44.880001 | 0.767142 | 0.200121 | 0.676439 | 0.670133 | 0.222252 |
| 1039 | Malawi | 2007 | 4.891037 | 6.741916 | 0.600267 | 46.259998 | 0.909994 | 0.202076 | 0.691305 | 0.727482 | 0.175514 |
| 1040 | Malawi | 2009 | 5.148240 | 6.838264 | 0.718450 | 49.020000 | 0.879161 | 0.175866 | 0.688926 | 0.765324 | 0.130396 |
| 1041 | Malawi | 2011 | 3.946063 | 6.894792 | 0.612737 | 51.419998 | 0.733464 | 0.098695 | 0.852994 | 0.712759 | 0.268475 |
| 1042 | Malawi | 2012 | 4.279270 | 6.884888 | 0.603726 | 52.439999 | 0.637363 | 0.169196 | 0.885785 | 0.815616 | 0.200463 |
| 1043 | Malawi | 2013 | 4.035084 | 6.907197 | 0.563162 | 53.459999 | 0.751995 | 0.078465 | 0.856666 | 0.808457 | 0.247829 |
| 1044 | Malawi | 2014 | 4.563080 | 6.934600 | 0.511616 | 54.480000 | 0.785767 | 0.061088 | 0.824018 | 0.703745 | 0.262713 |
| 1045 | Malawi | 2015 | 3.867638 | 6.934621 | 0.494382 | 55.500000 | 0.801391 | 0.058068 | 0.834825 | 0.632621 | 0.259764 |
| 1046 | Malawi | 2016 | 3.476493 | 6.932059 | 0.524300 | 56.200001 | 0.809884 | 0.065857 | 0.823615 | 0.603105 | 0.324739 |
| 1047 | Malawi | 2017 | 3.416863 | 6.944613 | 0.555423 | 56.900002 | 0.847921 | 0.024892 | 0.734637 | 0.608667 | 0.312088 |
| 1048 | Malawi | 2018 | 3.334634 | 6.949402 | 0.527843 | 57.599998 | 0.798915 | 0.072720 | 0.765964 | 0.586300 | 0.364894 |
| 1049 | Malawi | 2019 | 3.869124 | 6.965763 | 0.548956 | 58.299999 | 0.764864 | 0.003597 | 0.680248 | 0.536697 | 0.348162 |
| 1050 | Malaysia | 2006 | 6.011717 | 9.839272 | 0.865900 | 64.959999 | 0.836766 | 0.201140 | 0.739797 | 0.750243 | 0.242825 |
| 1051 | Malaysia | 2007 | 6.238904 | 9.880765 | 0.871497 | 65.120003 | 0.843628 | 0.089406 | 0.799052 | 0.775072 | 0.162262 |
| 1052 | Malaysia | 2008 | 5.806782 | 9.908837 | 0.802811 | 65.279999 | 0.779566 | 0.044362 | 0.883766 | 0.815414 | 0.185745 |
| 1053 | Malaysia | 2009 | 5.384702 | 9.875430 | 0.791666 | 65.440002 | 0.874320 | -0.008678 | 0.858095 | 0.821611 | 0.163550 |
| 1054 | Malaysia | 2010 | 5.580282 | 9.930140 | 0.839096 | 65.599998 | 0.769191 | 0.032386 | 0.843691 | 0.832448 | 0.191948 |
| 1055 | Malaysia | 2011 | 5.786367 | 9.966146 | 0.770423 | 65.760002 | 0.840359 | -0.016248 | 0.841505 | 0.887327 | 0.154875 |
| 1056 | Malaysia | 2012 | 5.914284 | 10.004979 | 0.841219 | 65.919998 | 0.848072 | 0.017118 | 0.846618 | 0.867353 | 0.176882 |
| 1057 | Malaysia | 2013 | 5.770200 | 10.037157 | 0.830900 | 66.080002 | 0.791310 | 0.264115 | 0.755383 | 0.736497 | 0.316552 |
| 1058 | Malaysia | 2014 | 5.962922 | 10.082084 | 0.863067 | 66.239998 | 0.808384 | 0.239343 | 0.844815 | 0.769534 | 0.260893 |
| 1059 | Malaysia | 2015 | 6.322121 | 10.118296 | 0.817616 | 66.400002 | 0.674594 | 0.222314 | 0.837892 | 0.774716 | 0.313733 |
| 1060 | Malaysia | 2018 | 5.338818 | 10.223283 | 0.789409 | 67.000000 | 0.874548 | 0.127355 | 0.894131 | 0.824455 | 0.200367 |
| 1061 | Malaysia | 2019 | 5.427954 | 10.252403 | 0.842499 | 67.199997 | 0.915779 | 0.123324 | 0.781944 | 0.834177 | 0.176072 |
| 1062 | Maldives | 2018 | 5.197575 | 9.825986 | 0.913315 | 70.599998 | 0.854759 | 0.023998 | NaN | NaN | NaN |
| 1063 | Mali | 2006 | 4.014076 | 7.592930 | 0.761116 | 45.919998 | 0.555076 | -0.071815 | 0.761046 | 0.766735 | 0.208563 |
| 1064 | Mali | 2008 | 4.114664 | 7.607233 | 0.746601 | 47.160000 | 0.494840 | -0.012124 | 0.917590 | 0.682154 | 0.164491 |
| 1065 | Mali | 2009 | 3.976599 | 7.621565 | 0.732557 | 47.779999 | 0.633816 | 0.008319 | 0.819208 | 0.760446 | 0.149751 |
| 1066 | Mali | 2010 | 3.762305 | 7.641754 | 0.750922 | 48.400002 | 0.749050 | -0.027935 | 0.810591 | 0.796525 | 0.161666 |
| 1067 | Mali | 2011 | 4.666833 | 7.642934 | 0.795505 | 48.759998 | 0.822848 | -0.100806 | 0.726062 | 0.758270 | 0.131821 |
| 1068 | Mali | 2012 | 4.313017 | 7.605007 | 0.823435 | 49.119999 | 0.704219 | -0.088333 | 0.786720 | 0.680750 | 0.109448 |
| 1069 | Mali | 2013 | 3.676277 | 7.598773 | 0.819691 | 49.480000 | 0.664711 | -0.053348 | 0.754807 | 0.723920 | 0.192901 |
| 1070 | Mali | 2014 | 3.974714 | 7.638360 | 0.843123 | 49.840000 | 0.651514 | -0.037456 | 0.657931 | 0.740901 | 0.185634 |
| 1071 | Mali | 2015 | 4.582098 | 7.668848 | 0.830189 | 50.200001 | 0.633754 | -0.067582 | 0.800047 | 0.708948 | 0.243003 |
| 1072 | Mali | 2016 | 4.016028 | 7.695135 | 0.836255 | 50.700001 | 0.696007 | -0.069865 | 0.862327 | 0.806901 | 0.305299 |
| 1073 | Mali | 2017 | 4.741850 | 7.717912 | 0.741359 | 51.200001 | 0.753213 | -0.069479 | 0.862655 | 0.741836 | 0.392784 |
| 1074 | Mali | 2018 | 4.415730 | 7.733290 | 0.691859 | 51.700001 | 0.737205 | -0.033900 | 0.793091 | 0.770017 | 0.369648 |
| 1075 | Mali | 2019 | 4.987992 | 7.752495 | 0.754558 | 52.200001 | 0.670405 | -0.037852 | 0.846340 | 0.711523 | 0.357765 |
| 1076 | Malta | 2009 | 6.327640 | 10.331231 | 0.915772 | 71.379997 | 0.803180 | 0.463617 | NaN | 0.714780 | 0.357874 |
| 1077 | Malta | 2010 | 5.773875 | 10.361134 | 0.908321 | 71.599998 | 0.802044 | 0.286807 | NaN | 0.696920 | 0.375303 |
| 1078 | Malta | 2011 | 6.154718 | 10.370396 | 0.922640 | 71.720001 | 0.881922 | 0.295860 | NaN | 0.736184 | 0.339703 |
| 1079 | Malta | 2012 | 5.962872 | 10.388962 | 0.921752 | 71.839996 | 0.860690 | 0.352201 | NaN | 0.744281 | 0.390504 |
| 1080 | Malta | 2013 | 6.379925 | 10.422175 | 0.942231 | 71.959999 | 0.909436 | 0.410022 | NaN | 0.660353 | 0.369558 |
| 1081 | Malta | 2014 | 6.452118 | 10.486463 | 0.941216 | 72.080002 | 0.903937 | 0.403982 | 0.669645 | 0.652304 | 0.352066 |
| 1082 | Malta | 2015 | 6.613394 | 10.565676 | 0.918765 | 72.199997 | 0.912178 | 0.347029 | 0.663886 | 0.679821 | 0.355041 |
| 1083 | Malta | 2016 | 6.590842 | 10.599454 | 0.930369 | 72.199997 | 0.916024 | 0.345397 | 0.696495 | 0.687272 | 0.355444 |
| 1084 | Malta | 2017 | 6.675666 | 10.634771 | 0.937332 | 72.199997 | 0.923643 | 0.252825 | 0.690495 | 0.720753 | 0.302443 |
| 1085 | Malta | 2018 | 6.909711 | 10.670444 | 0.931542 | 72.199997 | 0.927341 | 0.178772 | 0.595200 | 0.721224 | 0.295699 |
| 1086 | Malta | 2019 | 6.732977 | 10.676836 | 0.921579 | 72.199997 | 0.923967 | 0.087192 | 0.689411 | 0.706596 | 0.356244 |
| 1087 | Malta | 2020 | 6.156823 | NaN | 0.937920 | 72.199997 | 0.930600 | NaN | 0.674626 | 0.601496 | 0.410913 |
| 1088 | Mauritania | 2007 | 4.149043 | 8.533192 | 0.681909 | 53.660000 | 0.572888 | -0.071880 | 0.586451 | 0.732822 | 0.174229 |
| 1089 | Mauritania | 2008 | 4.248075 | 8.501031 | 0.670253 | 53.939999 | 0.593265 | -0.017986 | 0.840948 | 0.731891 | 0.176086 |
| 1090 | Mauritania | 2009 | 4.500432 | 8.472956 | 0.819334 | 54.220001 | 0.735071 | 0.039242 | 0.848294 | 0.737651 | 0.169829 |
| 1091 | Mauritania | 2010 | 4.772307 | 8.469553 | 0.856508 | 54.500000 | 0.668931 | 0.055054 | 0.727364 | 0.777994 | 0.128676 |
| 1092 | Mauritania | 2011 | 4.784804 | 8.480979 | 0.750277 | 54.820000 | 0.566920 | 0.051923 | 0.746938 | 0.762008 | 0.174863 |
| 1093 | Mauritania | 2012 | 4.673204 | 8.495164 | 0.763333 | 55.139999 | 0.487373 | -0.021221 | 0.707006 | 0.782068 | 0.163681 |
| 1094 | Mauritania | 2013 | 4.199015 | 8.506342 | 0.741156 | 55.459999 | 0.602800 | -0.078656 | 0.675554 | 0.793040 | 0.195690 |
| 1095 | Mauritania | 2014 | 4.482805 | 8.518929 | 0.852778 | 55.779999 | 0.468318 | -0.054140 | 0.589483 | 0.754968 | 0.163452 |
| 1096 | Mauritania | 2015 | 3.922664 | 8.542361 | 0.874946 | 56.099998 | 0.447087 | 0.055479 | 0.715358 | 0.819522 | 0.193900 |
| 1097 | Mauritania | 2016 | 4.472149 | 8.526330 | 0.784827 | 56.400002 | 0.466561 | -0.174851 | 0.841835 | 0.734556 | 0.221666 |
| 1098 | Mauritania | 2017 | 4.678160 | 8.532515 | 0.779225 | 56.700001 | 0.527447 | -0.152978 | 0.777314 | 0.637107 | 0.272322 |
| 1099 | Mauritania | 2018 | 4.313615 | 8.525642 | 0.801596 | 57.000000 | 0.466889 | -0.111638 | 0.710529 | 0.663382 | 0.275558 |
| 1100 | Mauritania | 2019 | 4.152619 | 8.555842 | 0.798102 | 57.299999 | 0.627505 | -0.101857 | 0.742890 | 0.691831 | 0.259739 |
| 1101 | Mauritius | 2011 | 5.477073 | 9.767368 | 0.800273 | 64.699997 | 0.848194 | 0.191429 | 0.846761 | 0.738434 | 0.252505 |
| 1102 | Mauritius | 2014 | 5.647780 | 9.864758 | 0.784822 | 65.300003 | 0.824230 | 0.176287 | 0.879406 | 0.808025 | 0.222400 |
| 1103 | Mauritius | 2016 | 5.610003 | 9.935322 | 0.836032 | 65.800003 | 0.819176 | 0.139464 | 0.890661 | 0.784898 | 0.245712 |
| 1104 | Mauritius | 2017 | 6.174118 | 9.971852 | 0.910142 | 66.099998 | 0.912308 | 0.086756 | 0.818180 | 0.747760 | 0.168721 |
| 1105 | Mauritius | 2018 | 5.881741 | 10.008217 | 0.908842 | 66.400002 | 0.866928 | -0.073091 | 0.785250 | 0.773952 | 0.157993 |
| 1106 | Mauritius | 2019 | 6.241165 | 10.042786 | 0.913134 | 66.699997 | 0.893158 | -0.052767 | 0.810201 | 0.808238 | 0.149363 |
| 1107 | Mauritius | 2020 | 6.015300 | 9.972017 | 0.892566 | 67.000000 | 0.842598 | -0.036693 | 0.771790 | 0.766984 | 0.138402 |
| 1108 | Mexico | 2005 | 6.580658 | 9.787807 | 0.902808 | 66.199997 | 0.813745 | NaN | 0.764249 | 0.819803 | 0.218943 |
| 1109 | Mexico | 2007 | 6.525378 | 9.825010 | 0.878806 | 66.320000 | 0.670430 | -0.094635 | 0.746681 | 0.815721 | 0.248498 |
| 1110 | Mexico | 2008 | 6.829036 | 9.821427 | 0.876328 | 66.379997 | 0.677477 | -0.127599 | 0.784898 | 0.825426 | 0.201175 |
| 1111 | Mexico | 2009 | 6.962819 | 9.752354 | 0.868221 | 66.440002 | 0.682463 | -0.075910 | 0.764226 | 0.848762 | 0.196071 |
| 1112 | Mexico | 2010 | 6.802389 | 9.787887 | 0.876390 | 66.500000 | 0.778121 | -0.048390 | 0.692892 | 0.840059 | 0.215495 |
| 1113 | Mexico | 2011 | 6.909515 | 9.809915 | 0.824064 | 66.680000 | 0.831368 | -0.099408 | 0.697580 | 0.790099 | 0.227556 |
| 1114 | Mexico | 2012 | 7.320185 | 9.832137 | 0.767279 | 66.860001 | 0.787768 | -0.092894 | 0.633281 | 0.784479 | 0.278111 |
| 1115 | Mexico | 2013 | 7.442546 | 9.832432 | 0.759138 | 67.040001 | 0.738717 | -0.164754 | 0.614747 | 0.789685 | 0.222949 |
| 1116 | Mexico | 2014 | 6.679831 | 9.847312 | 0.781965 | 67.220001 | 0.779133 | -0.094295 | 0.629851 | 0.801650 | 0.228730 |
| 1117 | Mexico | 2015 | 6.236287 | 9.867251 | 0.760614 | 67.400002 | 0.719466 | -0.151754 | 0.707972 | 0.744821 | 0.237188 |
| 1118 | Mexico | 2016 | 6.824173 | 9.883908 | 0.893493 | 67.699997 | 0.751613 | -0.153100 | 0.808579 | 0.859106 | 0.219571 |
| 1119 | Mexico | 2017 | 6.410299 | 9.893229 | 0.799839 | 68.000000 | 0.861405 | -0.201577 | 0.800893 | 0.842642 | 0.230991 |
| 1120 | Mexico | 2018 | 6.549579 | 9.903099 | 0.858069 | 68.300003 | 0.816200 | -0.179161 | 0.808638 | 0.881713 | 0.213254 |
| 1121 | Mexico | 2019 | 6.431945 | 9.890728 | 0.851686 | 68.599998 | 0.903384 | -0.140895 | 0.808538 | 0.864475 | 0.251983 |
| 1122 | Mexico | 2020 | 5.964221 | 9.782189 | 0.778816 | 68.900002 | 0.873347 | -0.119390 | 0.778166 | 0.810109 | 0.291556 |
| 1123 | Moldova | 2006 | 5.102071 | 8.935841 | 0.812183 | 60.580002 | 0.554478 | -0.164258 | 0.926055 | 0.618771 | 0.254923 |
| 1124 | Moldova | 2007 | 4.774918 | 8.967717 | 0.804192 | 60.759998 | 0.696195 | -0.185563 | 0.929560 | 0.571288 | 0.305512 |
| 1125 | Moldova | 2008 | 5.502756 | 9.044728 | 0.871553 | 60.939999 | 0.640617 | -0.055608 | 0.925664 | 0.583739 | 0.283589 |
| 1126 | Moldova | 2009 | 5.554374 | 8.984115 | 0.855883 | 61.119999 | 0.550859 | -0.098672 | 0.925062 | 0.561607 | 0.306488 |
| 1127 | Moldova | 2010 | 5.589736 | 9.053706 | 0.847095 | 61.299999 | 0.598485 | -0.088348 | 0.929309 | 0.583790 | 0.277520 |
| 1128 | Moldova | 2011 | 5.792263 | 9.110837 | 0.869414 | 61.619999 | 0.628023 | -0.081683 | 0.956644 | 0.567914 | 0.284829 |
| 1129 | Moldova | 2012 | 5.995713 | 9.105053 | 0.826220 | 61.939999 | 0.602419 | -0.049542 | 0.955485 | 0.567697 | 0.313726 |
| 1130 | Moldova | 2013 | 5.756059 | 9.191901 | 0.802883 | 62.259998 | 0.657734 | -0.068739 | 0.940632 | 0.581804 | 0.260603 |
| 1131 | Moldova | 2014 | 5.917058 | 9.241297 | 0.804969 | 62.580002 | 0.623186 | -0.113153 | 0.924807 | 0.582633 | 0.259690 |
| 1132 | Moldova | 2015 | 6.017472 | 9.245788 | 0.839906 | 62.900002 | 0.595241 | -0.089768 | 0.943119 | 0.590383 | 0.281456 |
| 1133 | Moldova | 2016 | 5.577784 | 9.300414 | 0.837321 | 63.599998 | 0.557369 | -0.047451 | 0.969483 | 0.621101 | 0.274551 |
| 1134 | Moldova | 2017 | 5.325531 | 9.363174 | 0.830768 | 64.300003 | 0.552825 | -0.052941 | 0.926334 | 0.581489 | 0.259478 |
| 1135 | Moldova | 2018 | 5.682277 | 9.423275 | 0.892080 | 65.000000 | 0.823824 | -0.084457 | 0.928720 | 0.581715 | 0.270072 |
| 1136 | Moldova | 2019 | 5.803451 | 9.475307 | 0.809167 | 65.699997 | 0.783665 | -0.092406 | 0.883823 | 0.630975 | 0.261621 |
| 1137 | Moldova | 2020 | 5.811629 | 9.462110 | 0.874062 | 66.400002 | 0.859083 | -0.058279 | 0.941439 | 0.727225 | 0.267836 |
| 1138 | Mongolia | 2007 | 4.609059 | 8.833219 | 0.881055 | 58.820000 | 0.781333 | 0.063611 | 0.917813 | 0.570640 | 0.203044 |
| 1139 | Mongolia | 2008 | 4.493010 | 8.903909 | 0.920116 | 59.279999 | 0.484081 | 0.067774 | 0.961714 | 0.585894 | 0.173452 |
| 1140 | Mongolia | 2010 | 4.585524 | 8.919961 | 0.904178 | 60.200001 | 0.630967 | 0.099294 | 0.927568 | 0.712425 | 0.150025 |
| 1141 | Mongolia | 2011 | 5.031174 | 9.061063 | 0.947885 | 60.500000 | 0.700346 | 0.150968 | 0.931159 | 0.692158 | 0.153233 |
| 1142 | Mongolia | 2012 | 4.885150 | 9.157819 | 0.918516 | 60.799999 | 0.688312 | 0.106601 | 0.932386 | 0.689053 | 0.181066 |
| 1143 | Mongolia | 2013 | 4.912928 | 9.247997 | 0.934742 | 61.099998 | 0.748014 | 0.136145 | 0.927854 | 0.649445 | 0.178902 |
| 1144 | Mongolia | 2014 | 4.824835 | 9.303862 | 0.943437 | 61.400002 | 0.752354 | 0.146183 | 0.908597 | 0.627492 | 0.170421 |
| 1145 | Mongolia | 2015 | 4.982720 | 9.307735 | 0.905524 | 61.700001 | 0.685511 | 0.173100 | 0.900218 | 0.652786 | 0.207653 |
| 1146 | Mongolia | 2016 | 5.057000 | 9.300219 | 0.947489 | 61.900002 | 0.759741 | 0.089747 | 0.900452 | 0.694095 | 0.171172 |
| 1147 | Mongolia | 2017 | 5.333850 | 9.333601 | 0.924251 | 62.099998 | 0.674627 | 0.118658 | 0.864952 | 0.675165 | 0.213600 |
| 1148 | Mongolia | 2018 | 5.464623 | 9.385602 | 0.941514 | 62.299999 | 0.695547 | 0.053941 | 0.848502 | 0.654125 | 0.191890 |
| 1149 | Mongolia | 2019 | 5.562905 | 9.418149 | 0.945758 | 62.500000 | 0.710675 | 0.148912 | 0.873167 | 0.707434 | 0.166921 |
| 1150 | Mongolia | 2020 | 6.011365 | 9.395559 | 0.917789 | 62.700001 | 0.718491 | 0.141357 | 0.842828 | 0.636443 | 0.259983 |
| 1151 | Montenegro | 2007 | 5.196315 | 9.692938 | 0.831841 | 66.199997 | 0.512067 | -0.133581 | 0.814568 | 0.578938 | 0.339851 |
| 1152 | Montenegro | 2009 | 4.801060 | 9.699058 | 0.815984 | 66.800003 | 0.556366 | -0.101294 | 0.838486 | 0.623211 | 0.422740 |
| 1153 | Montenegro | 2010 | 5.455030 | 9.724202 | 0.804549 | 67.099998 | 0.552104 | -0.206273 | 0.757207 | 0.594659 | 0.410302 |
| 1154 | Montenegro | 2011 | 5.223117 | 9.754926 | 0.817632 | 67.260002 | 0.546081 | -0.225963 | 0.762384 | 0.602761 | 0.378120 |
| 1155 | Montenegro | 2012 | 5.218724 | 9.726468 | 0.704033 | 67.419998 | 0.461706 | -0.192348 | 0.755060 | 0.573610 | 0.379281 |
| 1156 | Montenegro | 2013 | 5.074342 | 9.760366 | 0.735565 | 67.580002 | 0.502265 | -0.175839 | 0.693372 | 0.538980 | 0.331082 |
| 1157 | Montenegro | 2014 | 5.282721 | 9.777077 | 0.862930 | 67.739998 | 0.502666 | 0.096592 | 0.768466 | 0.587442 | 0.367647 |
| 1158 | Montenegro | 2015 | 5.124921 | 9.809857 | 0.739631 | 67.900002 | 0.583317 | -0.143989 | 0.781233 | 0.580314 | 0.337239 |
| 1159 | Montenegro | 2016 | 5.304066 | 9.838692 | 0.865744 | 68.099998 | 0.568634 | -0.087417 | 0.848967 | 0.591425 | 0.336675 |
| 1160 | Montenegro | 2017 | 5.614799 | 9.884665 | 0.881200 | 68.300003 | 0.625906 | -0.082894 | 0.755680 | 0.519128 | 0.349785 |
| 1161 | Montenegro | 2018 | 5.650190 | 9.934432 | 0.855980 | 68.500000 | 0.626431 | -0.051029 | 0.768923 | 0.589933 | 0.354935 |
| 1162 | Montenegro | 2019 | 5.386025 | 9.970144 | 0.831625 | 68.699997 | 0.694162 | -0.104814 | 0.819997 | 0.591094 | 0.365958 |
| 1163 | Montenegro | 2020 | 5.722163 | 9.912668 | 0.887129 | 68.900002 | 0.801855 | 0.059816 | 0.844687 | 0.603283 | 0.411378 |
| 1164 | Morocco | 2010 | 4.383247 | 8.745781 | NaN | 63.500000 | 0.662900 | -0.162347 | 0.900453 | NaN | NaN |
| 1165 | Morocco | 2011 | 5.084973 | 8.783417 | 0.833385 | 63.799999 | 0.578931 | -0.218117 | 0.875225 | 0.735656 | 0.187149 |
| 1166 | Morocco | 2012 | 4.969656 | 8.799099 | 0.675825 | 64.099998 | 0.756785 | -0.186699 | 0.844935 | 0.687131 | 0.281336 |
| 1167 | Morocco | 2013 | 5.142160 | 8.829243 | 0.597166 | 64.400002 | 0.571630 | -0.210398 | 0.771112 | 0.784261 | 0.239409 |
| 1168 | Morocco | 2015 | 5.163157 | 8.872023 | 0.605918 | 65.000000 | 0.712933 | -0.227693 | 0.841857 | 0.661078 | 0.261804 |
| 1169 | Morocco | 2016 | 5.386307 | 8.869151 | 0.655409 | 65.300003 | 0.816556 | -0.237478 | 0.717356 | 0.712659 | 0.205413 |
| 1170 | Morocco | 2017 | 5.312483 | 8.897567 | 0.641193 | 65.599998 | 0.814258 | -0.215847 | 0.840502 | 0.559288 | 0.322716 |
| 1171 | Morocco | 2018 | 4.896792 | 8.914309 | 0.553760 | 65.900002 | 0.773180 | -0.234374 | 0.843173 | 0.638049 | 0.415982 |
| 1172 | Morocco | 2019 | 5.056752 | 8.924619 | 0.534804 | 66.199997 | 0.756748 | -0.244314 | 0.756867 | 0.588883 | 0.409912 |
| 1173 | Morocco | 2020 | 4.802618 | 8.870917 | 0.552520 | 66.500000 | 0.818995 | -0.228578 | 0.802740 | 0.587182 | 0.256431 |
| 1174 | Mozambique | 2006 | 4.594880 | 6.775823 | 0.878795 | 44.799999 | 0.684149 | 0.041025 | 0.757999 | 0.622544 | 0.326823 |
| 1175 | Mozambique | 2007 | 4.832635 | 6.822544 | 0.747681 | 45.500000 | 0.643062 | 0.073758 | 0.854016 | 0.634451 | 0.240264 |
| 1176 | Mozambique | 2008 | 4.653583 | 6.865446 | 0.755583 | 46.200001 | 0.514437 | 0.005720 | 0.864335 | 0.622976 | 0.279546 |
| 1177 | Mozambique | 2011 | 4.971112 | 6.978660 | 0.817625 | 48.320000 | 0.639207 | -0.024201 | 0.718759 | 0.592006 | 0.243416 |
| 1178 | Mozambique | 2015 | 4.549767 | 7.140939 | 0.665858 | 51.200001 | 0.813229 | 0.088727 | 0.631573 | 0.564461 | 0.339584 |
| 1179 | Mozambique | 2017 | 4.279863 | 7.157471 | 0.678464 | 53.200001 | 0.822671 | -0.029965 | 0.682109 | 0.648381 | 0.353177 |
| 1180 | Mozambique | 2018 | 4.653714 | 7.162043 | 0.738480 | 54.200001 | 0.896622 | 0.048564 | 0.691220 | 0.639640 | 0.397279 |
| 1181 | Mozambique | 2019 | 4.932133 | 7.154967 | 0.742304 | 55.200001 | 0.869810 | 0.072745 | 0.681900 | 0.587275 | 0.384123 |
| 1182 | Myanmar | 2012 | 4.438940 | 8.157996 | 0.612250 | 57.020000 | 0.691094 | 0.644975 | 0.694739 | 0.764304 | 0.205414 |
| 1183 | Myanmar | 2013 | 4.175671 | 8.230396 | 0.756725 | 57.380001 | 0.775448 | 0.689318 | 0.637766 | 0.803302 | 0.217311 |
| 1184 | Myanmar | 2014 | 4.786247 | 8.299047 | 0.774267 | 57.740002 | NaN | 0.698099 | 0.591633 | 0.857965 | 0.111979 |
| 1185 | Myanmar | 2015 | 4.223846 | 8.359018 | 0.752064 | 58.099998 | 0.807971 | 0.687560 | 0.633305 | 0.865906 | 0.271751 |
| 1186 | Myanmar | 2016 | 4.623120 | 8.408031 | 0.793462 | 58.400002 | 0.877491 | 0.679426 | 0.607287 | 0.804010 | 0.301501 |
| 1187 | Myanmar | 2017 | 4.154342 | 8.463774 | 0.795184 | 58.700001 | 0.886012 | 0.650009 | 0.618822 | 0.745647 | 0.282286 |
| 1188 | Myanmar | 2018 | 4.410633 | 8.523012 | 0.773826 | 59.000000 | 0.906111 | 0.490355 | 0.646726 | 0.776951 | 0.300140 |
| 1189 | Myanmar | 2019 | 4.434237 | 8.545227 | 0.762995 | 59.299999 | 0.899064 | 0.561138 | 0.681796 | 0.754618 | 0.285576 |
| 1190 | Myanmar | 2020 | 4.431364 | 8.553914 | 0.795763 | 59.599998 | 0.824871 | 0.470258 | 0.646702 | 0.799749 | 0.289218 |
| 1191 | Namibia | 2007 | 4.885587 | 9.059242 | 0.827624 | 49.680000 | 0.781040 | -0.100627 | 0.839218 | 0.810895 | 0.159756 |
| 1192 | Namibia | 2014 | 4.573991 | 9.231745 | 0.762784 | 55.160000 | 0.849355 | -0.183334 | 0.790228 | 0.748637 | 0.238961 |
| 1193 | Namibia | 2017 | 4.441306 | 9.215378 | 0.828339 | 56.200001 | 0.810402 | -0.190043 | 0.831303 | 0.720678 | 0.277252 |
| 1194 | Namibia | 2018 | 4.834088 | 9.203514 | 0.864215 | 56.500000 | 0.753905 | -0.168838 | 0.845942 | 0.739387 | 0.240249 |
| 1195 | Namibia | 2019 | 4.435811 | 9.173384 | 0.844592 | 56.799999 | 0.739035 | -0.173687 | 0.879071 | 0.671533 | 0.256161 |
| 1196 | Namibia | 2020 | 4.451010 | 9.104139 | 0.740570 | 57.099998 | 0.665682 | -0.103880 | 0.810355 | 0.647920 | 0.247542 |
| 1197 | Nepal | 2006 | 4.566595 | 7.616336 | 0.873681 | 57.200001 | 0.689296 | NaN | 0.897137 | 0.716780 | 0.170838 |
| 1198 | Nepal | 2007 | 4.748284 | 7.637837 | 0.786708 | 57.700001 | 0.413321 | 0.316552 | 0.890811 | 0.643317 | 0.152298 |
| 1199 | Nepal | 2008 | 4.440526 | 7.686386 | 0.817658 | 58.200001 | 0.617605 | 0.290567 | 0.900029 | 0.744862 | 0.153098 |
| 1200 | Nepal | 2009 | 4.916868 | 7.722617 | 0.813068 | 58.700001 | 0.616154 | 0.043605 | 0.949702 | 0.570157 | 0.215434 |
| 1201 | Nepal | 2010 | 4.349675 | 7.764844 | 0.779038 | 59.200001 | 0.519063 | 0.091644 | 0.910802 | 0.672458 | 0.225973 |
| 1202 | Nepal | 2011 | 3.809445 | 7.797446 | 0.740979 | 59.400002 | 0.524798 | -0.009690 | 0.934564 | 0.699453 | 0.207359 |
| 1203 | Nepal | 2012 | 4.233245 | 7.846059 | 0.733602 | 59.599998 | 0.637778 | 0.070284 | 0.883494 | 0.736083 | 0.231071 |
| 1204 | Nepal | 2013 | 4.604577 | 7.889188 | 0.740099 | 59.799999 | 0.722266 | 0.150582 | 0.877340 | 0.629176 | 0.279264 |
| 1205 | Nepal | 2014 | 4.975015 | 7.947761 | 0.785883 | 60.000000 | 0.711878 | 0.120701 | 0.840686 | 0.613920 | 0.287447 |
| 1206 | Nepal | 2015 | 4.812437 | 7.976440 | 0.747612 | 60.200001 | 0.763447 | 0.227414 | 0.823508 | 0.543058 | 0.358234 |
| 1207 | Nepal | 2016 | 5.099540 | 7.973241 | 0.837044 | 61.299999 | 0.839488 | 0.168322 | 0.817115 | 0.627351 | 0.369662 |
| 1208 | Nepal | 2017 | 4.736692 | 8.038934 | 0.816383 | 62.400002 | 0.845148 | 0.133597 | 0.770177 | 0.570577 | 0.375978 |
| 1209 | Nepal | 2018 | 4.910087 | 8.087254 | 0.768336 | 63.500000 | 0.770094 | 0.122154 | 0.741753 | 0.536978 | 0.386792 |
| 1210 | Nepal | 2019 | 5.448725 | 8.136457 | 0.772273 | 64.599998 | 0.790348 | 0.166976 | 0.711842 | 0.535798 | 0.357100 |
| 1211 | Netherlands | 2005 | 7.463979 | 10.813766 | 0.947358 | 70.400002 | 0.901008 | NaN | 0.571342 | 0.869353 | 0.232795 |
| 1212 | Netherlands | 2007 | 7.451880 | 10.881042 | 0.943854 | 70.800003 | 0.896018 | 0.344347 | 0.445437 | 0.817750 | 0.213336 |
| 1213 | Netherlands | 2008 | 7.631012 | 10.898621 | 0.944202 | 71.000000 | 0.883287 | 0.365200 | 0.418940 | 0.788195 | 0.181690 |
| 1214 | Netherlands | 2010 | 7.501876 | 10.864328 | 0.956537 | 71.400002 | 0.921448 | 0.349346 | 0.398592 | 0.853234 | 0.206079 |
| 1215 | Netherlands | 2011 | 7.563798 | 10.875057 | 0.938396 | 71.519997 | 0.925432 | 0.335668 | 0.359396 | 0.862723 | 0.181386 |
| 1216 | Netherlands | 2012 | 7.470716 | 10.861000 | 0.938885 | 71.639999 | 0.877119 | 0.288119 | 0.433754 | 0.860641 | 0.226290 |
| 1217 | Netherlands | 2013 | 7.406550 | 10.856749 | 0.924705 | 71.760002 | 0.918996 | 0.304530 | 0.504530 | 0.866824 | 0.235443 |
| 1218 | Netherlands | 2014 | 7.321188 | 10.867284 | 0.908996 | 71.879997 | 0.910180 | 0.331311 | 0.456948 | 0.867766 | 0.220657 |
| 1219 | Netherlands | 2015 | 7.324437 | 10.882255 | 0.879010 | 72.000000 | 0.903979 | 0.261447 | 0.411822 | 0.834134 | 0.202129 |
| 1220 | Netherlands | 2016 | 7.540877 | 10.898613 | 0.925944 | 72.099998 | 0.907310 | 0.238664 | 0.433304 | 0.838432 | 0.214851 |
| 1221 | Netherlands | 2017 | 7.458965 | 10.921394 | 0.936501 | 72.199997 | 0.920320 | 0.250440 | 0.363134 | 0.852185 | 0.184520 |
| 1222 | Netherlands | 2018 | 7.463097 | 10.941197 | 0.939443 | 72.300003 | 0.919985 | 0.161489 | 0.370558 | 0.861977 | 0.204794 |
| 1223 | Netherlands | 2019 | 7.425269 | 10.953283 | 0.941477 | 72.400002 | 0.885593 | 0.212534 | 0.360068 | 0.838301 | 0.230502 |
| 1224 | Netherlands | 2020 | 7.504448 | 10.900500 | 0.943956 | 72.500000 | 0.934523 | 0.151298 | 0.280605 | 0.783991 | 0.246511 |
| 1225 | New Zealand | 2006 | 7.305014 | 10.525517 | 0.946047 | 71.199997 | 0.932080 | 0.311503 | 0.224220 | 0.879671 | 0.218773 |
| 1226 | New Zealand | 2007 | 7.604173 | 10.546432 | 0.966533 | 71.400002 | 0.878219 | 0.278680 | 0.294616 | 0.854027 | 0.237997 |
| 1227 | New Zealand | 2008 | 7.381171 | 10.527592 | 0.944275 | 71.599998 | 0.893072 | 0.297726 | 0.333751 | 0.854247 | 0.231881 |
| 1228 | New Zealand | 2010 | 7.223756 | 10.520456 | 0.975642 | 72.000000 | 0.917753 | 0.254364 | 0.320748 | 0.847234 | 0.234758 |
| 1229 | New Zealand | 2011 | 7.190638 | 10.536145 | 0.953650 | 72.120003 | 0.934769 | 0.284323 | 0.269330 | 0.863913 | 0.210150 |
| 1230 | New Zealand | 2012 | 7.249630 | 10.552812 | 0.930029 | 72.239998 | 0.901853 | 0.287335 | 0.289298 | 0.866304 | 0.206878 |
| 1231 | New Zealand | 2013 | 7.280152 | 10.571076 | 0.958153 | 72.360001 | 0.944000 | 0.236998 | 0.312236 | 0.834956 | 0.151397 |
| 1232 | New Zealand | 2014 | 7.305892 | 10.591587 | 0.942381 | 72.480003 | 0.931882 | 0.347953 | 0.272609 | 0.847514 | 0.199019 |
| 1233 | New Zealand | 2015 | 7.418121 | 10.608247 | 0.987343 | 72.599998 | 0.941784 | 0.329437 | 0.185889 | 0.833642 | 0.159830 |
| 1234 | New Zealand | 2016 | 7.225688 | 10.623369 | 0.936603 | 72.800003 | 0.926576 | 0.265629 | 0.278271 | 0.832945 | 0.207414 |
| 1235 | New Zealand | 2017 | 7.327183 | 10.633281 | 0.954921 | 73.000000 | 0.942279 | 0.294139 | 0.221887 | 0.817431 | 0.171717 |
| 1236 | New Zealand | 2018 | 7.370286 | 10.660436 | 0.953863 | 73.199997 | 0.949300 | 0.119827 | 0.206580 | 0.845363 | 0.167951 |
| 1237 | New Zealand | 2019 | 7.205174 | 10.666336 | 0.938821 | 73.400002 | 0.912042 | 0.156747 | 0.233831 | 0.816023 | 0.191176 |
| 1238 | New Zealand | 2020 | 7.257382 | 10.600457 | 0.951991 | 73.599998 | 0.918155 | 0.125260 | 0.282768 | 0.849415 | 0.208541 |
| 1239 | Nicaragua | 2006 | 4.460158 | 8.398162 | 0.877170 | 64.139999 | 0.745456 | 0.009666 | 0.844391 | 0.778861 | 0.294416 |
| 1240 | Nicaragua | 2007 | 4.944091 | 8.433932 | 0.866213 | 64.480003 | 0.835560 | 0.140392 | 0.825799 | 0.809762 | 0.287482 |
| 1241 | Nicaragua | 2008 | 5.103827 | 8.453972 | 0.857186 | 64.820000 | 0.790831 | 0.075514 | 0.818949 | 0.783848 | 0.289345 |
| 1242 | Nicaragua | 2009 | 5.352805 | 8.406804 | 0.834688 | 65.160004 | 0.746065 | 0.070269 | 0.794487 | 0.781097 | 0.299065 |
| 1243 | Nicaragua | 2010 | 5.686699 | 8.436372 | 0.863152 | 65.500000 | 0.791773 | 0.018256 | 0.801729 | 0.805376 | 0.268023 |
| 1244 | Nicaragua | 2011 | 5.385705 | 8.484162 | 0.800305 | 65.720001 | 0.778591 | -0.019579 | 0.760243 | 0.791432 | 0.309019 |
| 1245 | Nicaragua | 2012 | 5.448006 | 8.533731 | 0.894054 | 65.940002 | 0.850305 | 0.017166 | 0.643579 | 0.803254 | 0.254660 |
| 1246 | Nicaragua | 2013 | 5.772275 | 8.568552 | 0.868216 | 66.160004 | 0.859149 | 0.039189 | 0.636247 | 0.838620 | 0.270610 |
| 1247 | Nicaragua | 2014 | 6.275267 | 8.602145 | 0.838567 | 66.379997 | 0.817321 | 0.104033 | 0.698808 | 0.813284 | 0.333936 |
| 1248 | Nicaragua | 2015 | 5.924113 | 8.635926 | 0.826909 | 66.599998 | 0.809259 | 0.077173 | 0.727998 | 0.796685 | 0.345595 |
| 1249 | Nicaragua | 2016 | 6.012740 | 8.667662 | 0.852702 | 66.900002 | 0.716534 | 0.039407 | 0.731465 | 0.805124 | 0.380347 |
| 1250 | Nicaragua | 2017 | 6.476357 | 8.700187 | 0.838044 | 67.199997 | 0.922163 | 0.010172 | 0.672963 | 0.849764 | 0.308448 |
| 1251 | Nicaragua | 2018 | 5.818953 | 8.647322 | 0.854277 | 67.500000 | 0.797057 | 0.009082 | 0.712825 | 0.792649 | 0.408350 |
| 1252 | Nicaragua | 2019 | 6.112545 | 8.595469 | 0.873864 | 67.800003 | 0.882678 | 0.029247 | 0.621982 | 0.835423 | 0.337013 |
| 1253 | Niger | 2006 | 3.736952 | 6.887672 | 0.677166 | 46.360001 | 0.750336 | 0.076353 | 0.754975 | 0.755324 | 0.179304 |
| 1254 | Niger | 2007 | 4.277402 | 6.880663 | 0.725713 | 47.119999 | 0.584067 | -0.055892 | 0.747564 | 0.705617 | 0.158482 |
| 1255 | Niger | 2008 | 4.235657 | 6.917747 | 0.606639 | 47.880001 | 0.648728 | -0.054815 | 0.748753 | 0.649852 | 0.193882 |
| 1256 | Niger | 2009 | 4.267170 | 6.898063 | 0.771265 | 48.639999 | 0.880042 | -0.008599 | 0.483153 | 0.730271 | 0.115248 |
| 1257 | Niger | 2010 | 4.101016 | 6.940521 | 0.654965 | 49.400002 | 0.817220 | -0.023038 | 0.528980 | 0.745480 | 0.125838 |
| 1258 | Niger | 2011 | 4.555830 | 6.925129 | 0.817661 | 49.919998 | 0.779515 | -0.055358 | 0.549093 | 0.700494 | 0.166154 |
| 1259 | Niger | 2012 | 3.798088 | 6.986891 | 0.700108 | 50.439999 | 0.734431 | -0.063501 | 0.777341 | 0.602545 | 0.141553 |
| 1260 | Niger | 2013 | 3.716330 | 7.001983 | 0.695814 | 50.959999 | 0.825387 | -0.077427 | 0.710963 | 0.650200 | 0.208130 |
| 1261 | Niger | 2014 | 4.180943 | 7.026563 | 0.752534 | 51.480000 | 0.687634 | -0.046317 | 0.604728 | 0.677612 | 0.204661 |
| 1262 | Niger | 2015 | 3.671454 | 7.030498 | 0.713020 | 52.000000 | 0.728128 | -0.032141 | 0.702550 | 0.681873 | 0.218423 |
| 1263 | Niger | 2016 | 4.234646 | 7.047224 | 0.682828 | 52.500000 | 0.701927 | -0.015742 | 0.814494 | 0.674859 | 0.325442 |
| 1264 | Niger | 2017 | 4.615674 | 7.057603 | 0.582110 | 53.000000 | 0.683558 | -0.030251 | 0.777660 | 0.731161 | 0.426522 |
| 1265 | Niger | 2018 | 5.164007 | 7.087135 | 0.612026 | 53.500000 | 0.790666 | 0.008891 | 0.637167 | 0.770558 | 0.502555 |
| 1266 | Niger | 2019 | 5.003544 | 7.105849 | 0.676959 | 54.000000 | 0.831362 | 0.025960 | 0.728855 | 0.815915 | 0.304438 |
| 1267 | Nigeria | 2006 | 4.709746 | 8.326130 | 0.735179 | 44.119999 | 0.649140 | 0.084854 | 0.870749 | 0.781400 | 0.178237 |
| 1268 | Nigeria | 2007 | 4.890419 | 8.363639 | 0.717704 | 44.639999 | 0.635073 | 0.136394 | 0.918392 | 0.825709 | 0.141403 |
| 1269 | Nigeria | 2008 | 4.938560 | 8.402596 | 0.779640 | 45.160000 | 0.584222 | 0.119033 | 0.891890 | 0.739537 | 0.244094 |
| 1270 | Nigeria | 2009 | 4.980220 | 8.453269 | 0.722082 | 45.680000 | 0.536721 | 0.067498 | 0.913196 | 0.744715 | 0.225123 |
| 1271 | Nigeria | 2010 | 4.760276 | 8.503568 | 0.823823 | 46.200001 | 0.565351 | 0.066604 | 0.910719 | 0.782050 | 0.190343 |
| 1272 | Nigeria | 2012 | 5.492954 | 8.543129 | 0.817580 | 47.119999 | 0.651689 | 0.066321 | 0.900431 | 0.810906 | 0.209099 |
| 1273 | Nigeria | 2013 | 4.817869 | 8.580942 | 0.662943 | 47.580002 | 0.621588 | 0.050551 | 0.905309 | 0.638489 | 0.286346 |
| 1274 | Nigeria | 2015 | 4.932915 | 8.615186 | 0.811648 | 48.500000 | 0.680470 | -0.035358 | 0.926109 | 0.716892 | 0.251190 |
| 1275 | Nigeria | 2016 | 5.219568 | 8.572607 | 0.804767 | 48.900002 | 0.797691 | 0.043093 | 0.904707 | 0.731986 | 0.251836 |
| 1276 | Nigeria | 2017 | 5.321928 | 8.554557 | 0.733469 | 49.299999 | 0.825906 | 0.124339 | 0.834892 | 0.724991 | 0.235969 |
| 1277 | Nigeria | 2018 | 5.252288 | 8.547737 | 0.740854 | 49.700001 | 0.789881 | -0.010154 | 0.865603 | 0.805262 | 0.256470 |
| 1278 | Nigeria | 2019 | 4.356419 | 8.543932 | 0.733518 | 50.099998 | 0.729367 | 0.032285 | 0.873140 | 0.714991 | 0.245237 |
| 1279 | Nigeria | 2020 | 5.502948 | 8.484203 | 0.739289 | 50.500000 | 0.713062 | 0.099404 | 0.912774 | 0.743978 | 0.315887 |
| 1280 | North Cyprus | 2012 | 5.463305 | NaN | 0.871150 | NaN | 0.692568 | NaN | 0.854730 | 0.709236 | 0.405435 |
| 1281 | North Cyprus | 2013 | 5.566803 | NaN | 0.869274 | NaN | 0.775383 | NaN | 0.715356 | 0.621554 | 0.442972 |
| 1282 | North Cyprus | 2014 | 5.785979 | NaN | 0.801802 | NaN | 0.829677 | NaN | 0.692221 | 0.723842 | 0.311336 |
| 1283 | North Cyprus | 2015 | 5.842550 | NaN | 0.791383 | NaN | 0.785353 | NaN | 0.659180 | 0.701609 | 0.318930 |
| 1284 | North Cyprus | 2016 | 5.827128 | NaN | 0.807690 | NaN | 0.796234 | NaN | 0.670191 | 0.643664 | 0.346465 |
| 1285 | North Cyprus | 2018 | 5.608056 | NaN | 0.837392 | NaN | 0.797066 | NaN | 0.613837 | 0.480453 | 0.261868 |
| 1286 | North Cyprus | 2019 | 5.466615 | NaN | 0.803295 | NaN | 0.792735 | NaN | 0.640059 | 0.493693 | 0.296411 |
| 1287 | North Macedonia | 2007 | 4.493598 | 9.416016 | 0.810538 | 64.094666 | 0.439400 | 0.079752 | 0.869546 | 0.602946 | 0.251123 |
| 1288 | North Macedonia | 2009 | 4.428022 | 9.463950 | 0.734431 | 64.348663 | 0.552174 | -0.042020 | 0.843916 | 0.575552 | 0.370054 |
| 1289 | North Macedonia | 2010 | 4.180202 | 9.496163 | 0.686855 | 64.502441 | 0.513184 | -0.058499 | 0.856453 | 0.566944 | 0.313819 |
| 1290 | North Macedonia | 2011 | 4.898180 | 9.518450 | 0.784300 | 64.661400 | 0.607463 | -0.087268 | 0.865062 | 0.588337 | 0.362751 |
| 1291 | North Macedonia | 2012 | 4.639647 | 9.513014 | 0.798305 | 64.810860 | 0.613056 | -0.084414 | 0.919845 | 0.641887 | 0.421752 |
| 1292 | North Macedonia | 2013 | 5.186191 | 9.540985 | 0.832254 | 64.942177 | 0.640953 | 0.024604 | 0.860541 | 0.577912 | 0.330876 |
| 1293 | North Macedonia | 2014 | 5.203826 | 9.575810 | 0.792998 | 65.052765 | 0.644741 | 0.034639 | 0.860600 | 0.637328 | 0.306998 |
| 1294 | North Macedonia | 2015 | 4.975590 | 9.612898 | 0.766368 | 65.145203 | 0.660319 | -0.046562 | 0.824179 | 0.619699 | 0.299022 |
| 1295 | North Macedonia | 2016 | 5.345746 | 9.640300 | 0.871212 | 65.224686 | 0.706179 | 0.079814 | 0.869719 | 0.638737 | 0.292295 |
| 1296 | North Macedonia | 2017 | 5.233867 | 9.650458 | 0.799955 | 65.303299 | 0.752107 | -0.058800 | 0.855697 | 0.502460 | 0.299391 |
| 1297 | North Macedonia | 2018 | 5.239835 | 9.676835 | 0.848915 | 65.388832 | 0.744801 | -0.041357 | 0.909934 | 0.590138 | 0.298353 |
| 1298 | North Macedonia | 2019 | 5.015485 | 9.711485 | 0.814638 | 65.474358 | 0.724710 | 0.024419 | 0.922597 | 0.576300 | 0.303606 |
| 1299 | North Macedonia | 2020 | 5.053664 | 9.690015 | 0.750374 | 65.559883 | 0.787285 | 0.131274 | 0.877421 | 0.604627 | 0.365126 |
| 1300 | Norway | 2006 | 7.415682 | 11.030973 | 0.958511 | 71.320000 | 0.959533 | 0.108513 | 0.397150 | 0.831731 | 0.197113 |
| 1301 | Norway | 2008 | 7.632288 | 11.042418 | 0.935879 | 71.559998 | 0.947289 | 0.017757 | 0.502776 | 0.791722 | 0.155095 |
| 1302 | Norway | 2012 | 7.678277 | 11.017255 | 0.947657 | 72.239998 | 0.946566 | 0.147152 | 0.368043 | 0.822750 | 0.212821 |
| 1303 | Norway | 2014 | 7.444471 | 11.023678 | 0.941162 | 72.680000 | 0.956316 | 0.180976 | 0.404826 | 0.833697 | 0.194355 |
| 1304 | Norway | 2015 | 7.603434 | 11.033208 | 0.946834 | 72.900002 | 0.947621 | 0.256901 | 0.298814 | 0.842888 | 0.209410 |
| 1305 | Norway | 2016 | 7.596332 | 11.035056 | 0.959743 | 73.000000 | 0.954352 | 0.132863 | 0.409666 | 0.849626 | 0.209262 |
| 1306 | Norway | 2017 | 7.578745 | 11.049947 | 0.950128 | 73.099998 | 0.953017 | 0.236390 | 0.249711 | 0.849100 | 0.202914 |
| 1307 | Norway | 2018 | 7.444262 | 11.056159 | 0.965962 | 73.199997 | 0.960429 | 0.094059 | 0.268201 | 0.827414 | 0.211862 |
| 1308 | Norway | 2019 | 7.442140 | 11.060889 | 0.941784 | 73.300003 | 0.954044 | 0.110687 | 0.270572 | 0.822716 | 0.195487 |
| 1309 | Norway | 2020 | 7.290032 | 11.042160 | 0.955980 | 73.400002 | 0.964561 | 0.075149 | 0.271083 | 0.823094 | 0.216034 |
| 1310 | Oman | 2011 | 6.852982 | 10.382462 | NaN | 65.500000 | 0.916293 | 0.024908 | NaN | NaN | 0.295164 |
| 1311 | Pakistan | 2005 | 5.224658 | 8.217931 | 0.590946 | 54.200001 | 0.629996 | NaN | 0.844436 | NaN | 0.237266 |
| 1312 | Pakistan | 2007 | 5.671461 | 8.276694 | 0.478887 | 55.000000 | 0.395642 | 0.089101 | 0.793795 | 0.682748 | 0.310367 |
| 1313 | Pakistan | 2008 | 4.413919 | 8.270934 | 0.372908 | 55.400002 | 0.335224 | 0.100367 | 0.847683 | 0.655062 | 0.320658 |
| 1314 | Pakistan | 2009 | 5.208147 | 8.276524 | 0.521747 | 55.799999 | 0.387698 | 0.077099 | 0.873649 | 0.639216 | 0.348706 |
| 1315 | Pakistan | 2010 | 5.786133 | 8.270493 | 0.571316 | 56.200001 | 0.364206 | 0.300377 | 0.851656 | 0.650708 | 0.371941 |
| 1316 | Pakistan | 2011 | 5.267186 | 8.276015 | 0.509884 | 56.419998 | 0.375823 | 0.029676 | 0.857178 | 0.627774 | 0.357801 |
| 1317 | Pakistan | 2012 | 5.131565 | 8.289218 | 0.542038 | 56.639999 | 0.366844 | 0.164880 | 0.842025 | 0.664618 | 0.332448 |
| 1318 | Pakistan | 2013 | 5.138083 | 8.311207 | 0.607087 | 56.860001 | 0.447910 | 0.099550 | 0.791835 | 0.597887 | 0.273710 |
| 1319 | Pakistan | 2014 | 5.435658 | 8.335972 | 0.551683 | 57.080002 | 0.543139 | 0.140499 | 0.676928 | 0.584937 | 0.295480 |
| 1320 | Pakistan | 2015 | 4.823195 | 8.361321 | 0.561720 | 57.299999 | 0.586546 | 0.085402 | 0.716641 | 0.575255 | 0.328647 |
| 1321 | Pakistan | 2016 | 5.548508 | 8.394273 | 0.626921 | 57.700001 | 0.634183 | 0.094836 | 0.792530 | 0.647640 | 0.331617 |
| 1322 | Pakistan | 2017 | 5.830871 | 8.427578 | 0.690264 | 58.099998 | 0.712657 | 0.045268 | 0.713928 | 0.586167 | 0.308341 |
| 1323 | Pakistan | 2018 | 5.471554 | 8.463744 | 0.685059 | 58.500000 | 0.772569 | 0.068940 | 0.798842 | 0.567295 | 0.376706 |
| 1324 | Pakistan | 2019 | 4.442718 | 8.453291 | 0.617296 | 58.900002 | 0.684676 | 0.123729 | 0.775998 | 0.581067 | 0.424240 |
| 1325 | Palestinian Territories | 2006 | 4.716388 | 8.212757 | 0.817945 | 61.779999 | 0.546506 | NaN | 0.857824 | 0.497146 | 0.430580 |
| 1326 | Palestinian Territories | 2007 | 4.151054 | 8.218426 | 0.711819 | 61.897499 | 0.365296 | -0.080295 | 0.844180 | 0.566489 | 0.412328 |
| 1327 | Palestinian Territories | 2008 | 4.385603 | 8.275765 | 0.665911 | 62.014999 | 0.357757 | -0.069941 | 0.753213 | 0.571269 | 0.403283 |
| 1328 | Palestinian Territories | 2009 | 4.470191 | 8.328596 | 0.738077 | 62.132500 | 0.467812 | -0.085347 | 0.797354 | 0.544387 | 0.466428 |
| 1329 | Palestinian Territories | 2010 | 4.702604 | 8.383216 | 0.821746 | 62.250000 | 0.504262 | -0.117258 | 0.752415 | 0.627588 | 0.381490 |
| 1330 | Palestinian Territories | 2011 | 4.751220 | 8.474425 | 0.750832 | NaN | 0.521889 | -0.127053 | 0.750208 | 0.567007 | 0.387651 |
| 1331 | Palestinian Territories | 2012 | 4.646608 | 8.530910 | 0.782169 | NaN | 0.541583 | -0.153289 | 0.730194 | 0.616355 | 0.378504 |
| 1332 | Palestinian Territories | 2013 | 4.844028 | 8.488586 | 0.760900 | NaN | 0.453903 | -0.150118 | 0.779646 | 0.593701 | 0.365276 |
| 1333 | Palestinian Territories | 2014 | 4.721938 | 8.457089 | 0.775087 | NaN | 0.657050 | -0.146588 | 0.804165 | 0.565057 | 0.380452 |
| 1334 | Palestinian Territories | 2015 | 4.695239 | 8.480025 | 0.766101 | NaN | 0.556041 | -0.152813 | 0.774301 | 0.594456 | 0.369085 |
| 1335 | Palestinian Territories | 2016 | 4.906618 | 8.498220 | 0.817771 | NaN | 0.607669 | -0.128925 | 0.812465 | 0.592769 | 0.377642 |
| 1336 | Palestinian Territories | 2017 | 4.628133 | 8.484533 | 0.824345 | NaN | 0.631611 | -0.162522 | 0.830646 | 0.596766 | 0.416072 |
| 1337 | Palestinian Territories | 2018 | 4.553922 | NaN | 0.819479 | NaN | 0.654535 | NaN | 0.813780 | 0.610405 | 0.418929 |
| 1338 | Palestinian Territories | 2019 | 4.482537 | NaN | 0.832550 | NaN | 0.653488 | NaN | 0.829283 | 0.625176 | 0.399672 |
| 1339 | Panama | 2006 | 6.127988 | 9.763903 | 0.950980 | 67.900002 | 0.882047 | -0.047107 | 0.911756 | 0.845192 | 0.232063 |
| 1340 | Panama | 2007 | 6.894140 | 9.858971 | 0.937078 | 68.000000 | 0.640219 | 0.083109 | 0.915287 | 0.819987 | 0.149341 |
| 1341 | Panama | 2008 | 6.930903 | 9.935025 | 0.922481 | 68.099998 | 0.707385 | 0.059698 | 0.880651 | 0.819301 | 0.150143 |
| 1342 | Panama | 2009 | 7.033740 | 9.929617 | 0.905029 | 68.199997 | 0.721394 | 0.014429 | 0.889424 | 0.883028 | 0.144200 |
| 1343 | Panama | 2010 | 7.321467 | 9.968682 | 0.927533 | 68.300003 | 0.754524 | -0.008531 | 0.879826 | 0.887585 | 0.146369 |
| 1344 | Panama | 2011 | 7.248081 | 10.058502 | 0.876284 | 68.500000 | 0.829013 | 0.008965 | 0.839684 | 0.885293 | 0.179641 |
| 1345 | Panama | 2012 | 6.859836 | 10.134644 | 0.897391 | 68.699997 | 0.783183 | -0.001814 | 0.795797 | 0.868587 | 0.206641 |
| 1346 | Panama | 2013 | 6.866480 | 10.184355 | 0.895720 | 68.900002 | 0.811338 | 0.018312 | 0.814465 | 0.868715 | 0.225746 |
| 1347 | Panama | 2014 | 6.631171 | 10.216750 | 0.873474 | 69.099998 | 0.893915 | 0.002134 | 0.846594 | 0.807690 | 0.253816 |
| 1348 | Panama | 2015 | 6.605550 | 10.255424 | 0.882615 | 69.300003 | 0.846669 | -0.006958 | 0.809943 | 0.800634 | 0.263826 |
| 1349 | Panama | 2016 | 6.117638 | 10.286634 | 0.882460 | 69.400002 | 0.884480 | -0.102454 | 0.836977 | 0.857624 | 0.244132 |
| 1350 | Panama | 2017 | 6.567659 | 10.323997 | 0.911905 | 69.500000 | 0.899574 | -0.169566 | 0.840777 | 0.832689 | 0.242319 |
| 1351 | Panama | 2018 | 6.281434 | 10.343328 | 0.904390 | 69.599998 | 0.861448 | -0.130710 | 0.836931 | 0.883581 | 0.222599 |
| 1352 | Panama | 2019 | 6.085955 | 10.356431 | 0.885721 | 69.699997 | 0.882961 | -0.198985 | 0.868828 | 0.877562 | 0.243567 |
| 1353 | Paraguay | 2006 | 4.730082 | 9.087580 | 0.895428 | 63.619999 | 0.691022 | 0.066075 | 0.840989 | 0.815584 | 0.302746 |
| 1354 | Paraguay | 2007 | 5.272461 | 9.126068 | 0.862656 | 63.840000 | 0.698988 | 0.132008 | 0.929891 | 0.866669 | 0.218699 |
| 1355 | Paraguay | 2008 | 5.570062 | 9.173999 | 0.889281 | 64.059998 | 0.649069 | 0.056645 | 0.891085 | 0.848840 | 0.259038 |
| 1356 | Paraguay | 2009 | 5.576147 | 9.157912 | 0.900354 | 64.279999 | 0.717870 | 0.027380 | 0.857340 | 0.831757 | 0.186126 |
| 1357 | Paraguay | 2010 | 5.841174 | 9.250023 | 0.889153 | 64.500000 | 0.726262 | 0.076352 | 0.779915 | 0.855230 | 0.175859 |
| 1358 | Paraguay | 2011 | 5.677081 | 9.277973 | 0.869150 | 64.620003 | 0.665864 | 0.190680 | 0.755997 | 0.809841 | 0.190263 |
| 1359 | Paraguay | 2012 | 5.820058 | 9.258847 | 0.931005 | 64.739998 | 0.748207 | 0.199644 | 0.773659 | 0.837175 | 0.212839 |
| 1360 | Paraguay | 2013 | 5.936241 | 9.325938 | 0.938647 | 64.860001 | 0.908906 | 0.045610 | 0.902551 | 0.918937 | 0.223824 |
| 1361 | Paraguay | 2014 | 5.118642 | 9.359787 | 0.959250 | 64.980003 | 0.759396 | -0.001600 | 0.762376 | 0.943621 | 0.215778 |
| 1362 | Paraguay | 2015 | 5.559724 | 9.376698 | 0.914199 | 65.099998 | 0.806125 | -0.007562 | 0.862888 | 0.866218 | 0.218508 |
| 1363 | Paraguay | 2016 | 5.801380 | 9.405685 | 0.939867 | 65.300003 | 0.853534 | -0.070965 | 0.756116 | 0.924561 | 0.197176 |
| 1364 | Paraguay | 2017 | 5.713295 | 9.441003 | 0.902043 | 65.500000 | 0.891171 | 0.003110 | 0.809901 | 0.902772 | 0.231784 |
| 1365 | Paraguay | 2019 | 5.652626 | 9.448144 | 0.892487 | 65.900002 | 0.876053 | 0.028113 | 0.881786 | 0.857724 | 0.275187 |
| 1366 | Peru | 2006 | 4.810845 | 8.989351 | 0.874650 | 65.339996 | 0.667579 | -0.071212 | 0.895348 | 0.696759 | 0.419590 |
| 1367 | Peru | 2007 | 5.213962 | 9.062915 | 0.756370 | 65.580002 | 0.638497 | -0.077587 | 0.930641 | 0.757589 | 0.361295 |
| 1368 | Peru | 2008 | 5.129231 | 9.142194 | 0.777107 | 65.820000 | 0.637672 | -0.067072 | 0.896440 | 0.762631 | 0.353950 |
| 1369 | Peru | 2009 | 5.518847 | 9.145060 | 0.798696 | 66.059998 | 0.638375 | -0.079135 | 0.880334 | 0.810965 | 0.320298 |
| 1370 | Peru | 2010 | 5.612785 | 9.216966 | 0.811914 | 66.300003 | 0.756706 | -0.060438 | 0.880594 | 0.799534 | 0.330243 |
| 1371 | Peru | 2011 | 5.892457 | 9.270197 | 0.756305 | 66.480003 | 0.772759 | -0.123341 | 0.823665 | 0.780169 | 0.330921 |
| 1372 | Peru | 2012 | 5.824557 | 9.321531 | 0.764072 | 66.660004 | 0.703001 | -0.079390 | 0.866838 | 0.757178 | 0.397959 |
| 1373 | Peru | 2013 | 5.782557 | 9.369393 | 0.796768 | 66.839996 | 0.703041 | -0.066112 | 0.869899 | 0.778473 | 0.390038 |
| 1374 | Peru | 2014 | 5.865816 | 9.382366 | 0.818987 | 67.019997 | 0.722352 | -0.136349 | 0.877822 | 0.758988 | 0.319338 |
| 1375 | Peru | 2015 | 5.577263 | 9.401809 | 0.798418 | 67.199997 | 0.802269 | -0.089997 | 0.883730 | 0.753556 | 0.378305 |
| 1376 | Peru | 2016 | 5.700629 | 9.425749 | 0.802856 | 67.500000 | 0.829844 | -0.134056 | 0.865920 | 0.821675 | 0.338007 |
| 1377 | Peru | 2017 | 5.710937 | 9.434006 | 0.830123 | 67.800003 | 0.826552 | -0.154364 | 0.895384 | 0.789391 | 0.393874 |
| 1378 | Peru | 2018 | 5.679661 | 9.455823 | 0.845301 | 68.099998 | 0.829642 | -0.178486 | 0.906245 | 0.808621 | 0.380033 |
| 1379 | Peru | 2019 | 5.999382 | 9.460935 | 0.809076 | 68.400002 | 0.814806 | -0.129736 | 0.873602 | 0.820448 | 0.374985 |
| 1380 | Philippines | 2006 | 4.669946 | 8.561845 | 0.795313 | 59.799999 | 0.828273 | 0.063402 | 0.841299 | 0.831999 | NaN |
| 1381 | Philippines | 2007 | 5.073562 | 8.607889 | 0.800711 | 60.000000 | 0.851566 | -0.021588 | 0.880246 | 0.784118 | 0.378188 |
| 1382 | Philippines | 2008 | 4.589065 | 8.633818 | 0.798442 | 60.200001 | 0.860843 | 0.082775 | 0.816585 | 0.805394 | 0.384015 |
| 1383 | Philippines | 2009 | 4.879911 | 8.631698 | 0.775171 | 60.400002 | 0.873605 | 0.003718 | 0.804578 | 0.846068 | 0.311330 |
| 1384 | Philippines | 2010 | 4.941514 | 8.685817 | 0.804861 | 60.599998 | 0.893351 | 0.033068 | 0.812448 | 0.875529 | 0.293918 |
| 1385 | Philippines | 2011 | 4.993957 | 8.706756 | 0.788763 | 60.799999 | 0.882837 | 0.072544 | 0.782946 | 0.851472 | 0.358326 |
| 1386 | Philippines | 2012 | 5.001965 | 8.756410 | 0.812922 | 61.000000 | 0.914500 | 0.052633 | 0.771168 | 0.865131 | 0.351125 |
| 1387 | Philippines | 2013 | 4.976925 | 8.804813 | 0.846413 | 61.200001 | 0.907458 | 0.021115 | 0.756389 | 0.799079 | 0.331958 |
| 1388 | Philippines | 2014 | 5.312550 | 8.849893 | 0.813300 | 61.400002 | 0.902186 | -0.015336 | 0.787219 | 0.813342 | 0.334037 |
| 1389 | Philippines | 2015 | 5.547489 | 8.895648 | 0.853589 | 61.599998 | 0.911534 | -0.051160 | 0.755192 | 0.805238 | 0.350588 |
| 1390 | Philippines | 2016 | 5.430833 | 8.949631 | 0.821299 | 61.700001 | 0.907596 | -0.071243 | 0.791962 | 0.820969 | 0.290233 |
| 1391 | Philippines | 2017 | 5.594270 | 9.002189 | 0.851029 | 61.799999 | 0.925703 | -0.141393 | 0.711166 | 0.768981 | 0.340622 |
| 1392 | Philippines | 2018 | 5.869173 | 9.049713 | 0.845803 | 61.900002 | 0.917808 | -0.107958 | 0.726483 | 0.772846 | 0.393481 |
| 1393 | Philippines | 2019 | 6.267745 | 9.094725 | 0.845095 | 62.000000 | 0.909599 | -0.082581 | 0.748442 | 0.780897 | 0.340569 |
| 1394 | Philippines | 2020 | 5.079585 | 9.061443 | 0.781140 | 62.099998 | 0.932042 | -0.115543 | 0.744284 | 0.803562 | 0.326889 |
| 1395 | Poland | 2005 | 5.587209 | 9.848785 | 0.921528 | 66.300003 | 0.782473 | NaN | 0.982931 | 0.715111 | 0.282439 |
| 1396 | Poland | 2007 | 5.886137 | 9.977909 | 0.912640 | 66.699997 | 0.772223 | -0.047307 | 0.925286 | 0.760026 | 0.237599 |
| 1397 | Poland | 2009 | 5.772027 | 10.046525 | 0.916798 | 67.099998 | 0.820649 | 0.073213 | 0.897762 | 0.690351 | 0.245965 |
| 1398 | Poland | 2010 | 5.887030 | 10.084822 | 0.955065 | 67.300003 | 0.794900 | 0.001657 | 0.904697 | 0.736898 | 0.234237 |
| 1399 | Poland | 2011 | 5.646205 | 10.133238 | 0.904579 | 67.459999 | 0.868149 | -0.066878 | 0.907953 | 0.725360 | 0.223810 |
| 1400 | Poland | 2012 | 5.875932 | 10.149192 | 0.935924 | 67.620003 | 0.811302 | -0.026550 | 0.887896 | 0.787489 | 0.266747 |
| 1401 | Poland | 2013 | 5.746132 | 10.163618 | 0.911935 | 67.779999 | 0.775931 | -0.137175 | 0.915677 | 0.784124 | 0.241981 |
| 1402 | Poland | 2014 | 5.750282 | 10.197012 | 0.923642 | 67.940002 | 0.875357 | -0.064226 | 0.897742 | 0.776997 | 0.222644 |
| 1403 | Poland | 2015 | 6.007022 | 10.235351 | 0.893090 | 68.099998 | 0.793462 | -0.093017 | 0.810096 | 0.734383 | 0.240432 |
| 1404 | Poland | 2016 | 6.162076 | 10.265960 | 0.917399 | 68.500000 | 0.870708 | -0.090938 | 0.847754 | 0.776625 | 0.223536 |
| 1405 | Poland | 2017 | 6.201268 | 10.314032 | 0.881854 | 68.900002 | 0.830843 | -0.121764 | 0.639480 | 0.677436 | 0.203388 |
| 1406 | Poland | 2018 | 6.111485 | 10.366142 | 0.863444 | 69.300003 | 0.870215 | -0.254441 | 0.720451 | 0.742415 | 0.176011 |
| 1407 | Poland | 2019 | 6.242094 | 10.406878 | 0.878268 | 69.699997 | 0.882886 | -0.230718 | 0.696057 | 0.725160 | 0.168090 |
| 1408 | Poland | 2020 | 6.139455 | 10.371203 | 0.953172 | 70.099998 | 0.767429 | -0.006559 | 0.786874 | 0.759843 | 0.328938 |
| 1409 | Portugal | 2006 | 5.405246 | 10.359779 | 0.905290 | 69.839996 | 0.882068 | -0.178589 | 0.880059 | 0.708912 | 0.333498 |
| 1410 | Portugal | 2008 | 5.716967 | 10.384319 | 0.885925 | 70.320000 | 0.646464 | -0.217483 | 0.932686 | 0.702931 | 0.309281 |
| 1411 | Portugal | 2010 | 5.094526 | 10.368415 | 0.863907 | 70.800003 | 0.721036 | -0.105990 | 0.947879 | 0.741612 | 0.265107 |
| 1412 | Portugal | 2011 | 5.219998 | 10.352778 | 0.855961 | 71.000000 | 0.875093 | -0.173062 | 0.961977 | 0.725109 | 0.279201 |
| 1413 | Portugal | 2012 | 4.993962 | 10.315413 | 0.866039 | 71.199997 | 0.773821 | -0.097088 | 0.959288 | 0.728934 | 0.370170 |
| 1414 | Portugal | 2013 | 5.157688 | 10.311633 | 0.867181 | 71.400002 | 0.788033 | -0.118447 | 0.946257 | 0.699667 | 0.347898 |
| 1415 | Portugal | 2014 | 5.126912 | 10.324915 | 0.861829 | 71.599998 | 0.846810 | -0.126404 | 0.941070 | 0.705072 | 0.357692 |
| 1416 | Portugal | 2015 | 5.080866 | 10.346819 | 0.866214 | 71.800003 | 0.800440 | -0.163106 | 0.941051 | 0.657176 | 0.370737 |
| 1417 | Portugal | 2016 | 5.446637 | 10.369967 | 0.904635 | 72.000000 | 0.838069 | -0.225286 | 0.922192 | 0.683566 | 0.326253 |
| 1418 | Portugal | 2017 | 5.711499 | 10.406869 | 0.899985 | 72.199997 | 0.905066 | -0.175874 | 0.880971 | 0.649151 | 0.294273 |
| 1419 | Portugal | 2018 | 5.919823 | 10.434500 | 0.887113 | 72.400002 | 0.877404 | -0.261366 | 0.879728 | 0.679104 | 0.317995 |
| 1420 | Portugal | 2019 | 6.095473 | 10.457315 | 0.876083 | 72.599998 | 0.882351 | -0.233855 | 0.915166 | 0.709822 | 0.299875 |
| 1421 | Portugal | 2020 | 5.767792 | 10.370820 | 0.874990 | 72.800003 | 0.913131 | -0.238090 | 0.867157 | 0.647769 | 0.382813 |
| 1422 | Qatar | 2009 | 6.417824 | 11.455724 | 0.894493 | 66.580002 | 0.864992 | 0.234897 | 0.183798 | 0.677912 | 0.258085 |
| 1423 | Qatar | 2010 | 6.849653 | 11.519814 | NaN | 66.699997 | NaN | 0.103687 | NaN | NaN | NaN |
| 1424 | Qatar | 2011 | 6.591604 | 11.553021 | 0.857351 | 67.019997 | 0.904687 | 0.011700 | NaN | 0.760927 | 0.327790 |
| 1425 | Qatar | 2012 | 6.611299 | 11.523082 | 0.838132 | 67.339996 | 0.924334 | 0.161530 | NaN | 0.765899 | 0.322181 |
| 1426 | Qatar | 2015 | 6.374529 | 11.485615 | NaN | 68.300003 | NaN | NaN | NaN | NaN | NaN |
| 1427 | Romania | 2005 | 5.048648 | 9.724312 | 0.837685 | 64.000000 | 0.800121 | NaN | 0.956885 | 0.642016 | 0.345687 |
| 1428 | Romania | 2007 | 5.393724 | 9.892077 | 0.736480 | 64.480003 | 0.685748 | -0.187757 | 0.948707 | 0.644178 | 0.276626 |
| 1429 | Romania | 2009 | 5.367565 | 9.949312 | 0.812450 | 64.959999 | 0.605828 | -0.196232 | 0.966795 | 0.548347 | 0.270051 |
| 1430 | Romania | 2010 | 4.909166 | 9.915458 | 0.689066 | 65.199997 | 0.565537 | -0.084713 | 0.973686 | 0.596489 | 0.344478 |
| 1431 | Romania | 2011 | 5.022758 | 9.940249 | 0.752607 | 65.419998 | 0.650402 | -0.139793 | 0.964043 | 0.542729 | 0.294462 |
| 1432 | Romania | 2012 | 5.166875 | 9.965261 | 0.740043 | 65.639999 | 0.644536 | -0.111523 | 0.959486 | 0.555994 | 0.342615 |
| 1433 | Romania | 2013 | 5.081584 | 10.003515 | 0.777552 | 65.860001 | 0.654542 | -0.129216 | 0.951844 | 0.639821 | 0.328619 |
| 1434 | Romania | 2014 | 5.726893 | 10.040800 | 0.752941 | 66.080002 | 0.754236 | -0.100443 | 0.958325 | 0.654498 | 0.330688 |
| 1435 | Romania | 2015 | 5.777491 | 10.083486 | 0.786967 | 66.300003 | 0.795848 | -0.141258 | 0.961651 | 0.714146 | 0.311574 |
| 1436 | Romania | 2016 | 5.968871 | 10.136113 | 0.809229 | 66.599998 | 0.821721 | -0.115288 | 0.949045 | 0.694415 | 0.257764 |
| 1437 | Romania | 2017 | 6.089905 | 10.210666 | 0.811240 | 66.900002 | 0.838587 | -0.159790 | 0.925658 | 0.733730 | 0.230836 |
| 1438 | Romania | 2018 | 6.150879 | 10.259953 | 0.817930 | 67.199997 | 0.845160 | -0.217366 | 0.921170 | 0.735343 | 0.298454 |
| 1439 | Romania | 2019 | 6.129942 | 10.305914 | 0.841906 | 67.500000 | 0.847543 | -0.221422 | 0.954131 | 0.697443 | 0.243659 |
| 1440 | Russia | 2006 | 4.963743 | 9.990775 | 0.894707 | 58.680000 | 0.643388 | -0.306562 | 0.935102 | 0.611432 | 0.232429 |
| 1441 | Russia | 2007 | 5.222867 | 10.074066 | 0.884656 | 59.259998 | 0.592570 | -0.283742 | 0.933464 | 0.622690 | 0.192846 |
| 1442 | Russia | 2008 | 5.618754 | 10.125198 | 0.882316 | 59.840000 | 0.642778 | -0.305012 | 0.924090 | 0.593798 | 0.165902 |
| 1443 | Russia | 2009 | 5.158228 | 10.043687 | 0.908076 | 60.419998 | 0.617115 | -0.283383 | 0.953602 | 0.566151 | 0.168979 |
| 1444 | Russia | 2010 | 5.384773 | 10.087255 | 0.908814 | 61.000000 | 0.613159 | -0.296366 | 0.936572 | 0.588975 | 0.171421 |
| 1445 | Russia | 2011 | 5.388766 | 10.128576 | 0.883417 | 61.419998 | 0.625848 | -0.278831 | 0.935130 | 0.601348 | 0.165235 |
| 1446 | Russia | 2012 | 5.620736 | 10.166346 | 0.901295 | 61.840000 | 0.609104 | -0.292616 | 0.937518 | 0.611164 | 0.173604 |
| 1447 | Russia | 2013 | 5.537178 | 10.181619 | 0.880857 | 62.259998 | 0.661186 | -0.289330 | 0.933805 | 0.679745 | 0.179924 |
| 1448 | Russia | 2014 | 6.036977 | 10.171111 | 0.931755 | 62.680000 | 0.744332 | -0.264560 | 0.869267 | 0.687638 | 0.151347 |
| 1449 | Russia | 2015 | 5.995539 | 10.149030 | 0.924363 | 63.099998 | 0.685455 | -0.171061 | 0.913418 | 0.678732 | 0.130006 |
| 1450 | Russia | 2016 | 5.854946 | 10.149133 | 0.910927 | 63.500000 | 0.713606 | -0.181247 | 0.925463 | 0.636299 | 0.142497 |
| 1451 | Russia | 2017 | 5.578743 | 10.166081 | 0.896151 | 63.900002 | 0.730874 | -0.144961 | 0.861590 | 0.710230 | 0.194561 |
| 1452 | Russia | 2018 | 5.513500 | 10.191209 | 0.908726 | 64.300003 | 0.729282 | -0.147142 | 0.865312 | 0.673346 | 0.198796 |
| 1453 | Russia | 2019 | 5.440524 | 10.205218 | 0.910099 | 64.699997 | 0.714766 | -0.115572 | 0.847705 | 0.691351 | 0.200422 |
| 1454 | Russia | 2020 | 5.495289 | 10.162235 | 0.887020 | 65.099998 | 0.714466 | -0.070612 | 0.823048 | 0.645215 | 0.189522 |
| 1455 | Rwanda | 2006 | 4.214704 | 7.111424 | 0.717583 | 49.880001 | 0.915481 | NaN | 0.298644 | 0.735016 | 0.188996 |
| 1456 | Rwanda | 2008 | 4.362989 | 7.238954 | 0.485681 | 53.040001 | 0.752293 | 0.017381 | 0.286407 | 0.642954 | 0.220768 |
| 1457 | Rwanda | 2009 | 4.029762 | 7.272810 | 0.559390 | 54.619999 | 0.765569 | -0.000730 | 0.409703 | 0.677698 | 0.112362 |
| 1458 | Rwanda | 2011 | 4.097436 | 7.369293 | 0.569860 | 56.820000 | 0.829036 | -0.038671 | 0.161475 | 0.665474 | 0.154242 |
| 1459 | Rwanda | 2012 | 3.333048 | 7.427577 | 0.637147 | 57.439999 | 0.835491 | -0.011818 | 0.081325 | 0.702794 | 0.132398 |
| 1460 | Rwanda | 2013 | 3.466388 | 7.449177 | 0.749633 | 58.060001 | 0.904272 | -0.027710 | 0.117165 | 0.760014 | 0.167348 |
| 1461 | Rwanda | 2014 | 3.595678 | 7.484139 | 0.748304 | 58.680000 | 0.894025 | -0.022729 | 0.078000 | 0.762844 | 0.133610 |
| 1462 | Rwanda | 2015 | 3.483109 | 7.543681 | 0.678144 | 59.299999 | 0.907892 | 0.025019 | 0.094604 | 0.721183 | 0.206403 |
| 1463 | Rwanda | 2016 | 3.332990 | 7.575755 | 0.665131 | 59.900002 | 0.910736 | 0.025147 | 0.158601 | 0.752311 | 0.285384 |
| 1464 | Rwanda | 2017 | 3.108374 | 7.588451 | 0.516550 | 60.500000 | 0.908115 | 0.051390 | 0.213757 | 0.762161 | 0.358310 |
| 1465 | Rwanda | 2018 | 3.561047 | 7.644233 | 0.616173 | 61.099998 | 0.924232 | 0.056992 | 0.163810 | 0.793368 | 0.308199 |
| 1466 | Rwanda | 2019 | 3.268152 | 7.708061 | 0.489458 | 61.700001 | 0.868999 | 0.064066 | 0.167971 | 0.736068 | 0.417668 |
| 1467 | Saudi Arabia | 2005 | 7.079644 | 10.698955 | 0.867819 | 63.500000 | NaN | NaN | 0.505149 | 0.729598 | 0.242553 |
| 1468 | Saudi Arabia | 2007 | 7.266694 | 10.688892 | 0.891525 | 63.860001 | 0.622070 | 0.004603 | NaN | 0.772243 | 0.231547 |
| 1469 | Saudi Arabia | 2008 | 6.811370 | 10.721947 | 0.823054 | 64.040001 | 0.531812 | -0.021993 | 0.507919 | 0.709539 | 0.201823 |
| 1470 | Saudi Arabia | 2009 | 6.147590 | 10.672890 | 0.921288 | 64.220001 | 0.639406 | -0.109878 | 0.445132 | 0.741836 | 0.319475 |
| 1471 | Saudi Arabia | 2010 | 6.307098 | 10.692780 | 0.879598 | 64.400002 | 0.677777 | -0.032633 | NaN | 0.645089 | 0.297209 |
| 1472 | Saudi Arabia | 2011 | 6.699790 | 10.757668 | 0.829634 | 64.599998 | 0.603456 | -0.141886 | NaN | 0.725971 | 0.240140 |
| 1473 | Saudi Arabia | 2012 | 6.396359 | 10.779456 | 0.867101 | 64.800003 | 0.560455 | -0.119506 | NaN | 0.715217 | 0.224841 |
| 1474 | Saudi Arabia | 2013 | 6.495133 | 10.775777 | 0.826695 | 65.000000 | 0.661042 | -0.081083 | NaN | 0.744080 | 0.275550 |
| 1475 | Saudi Arabia | 2014 | 6.278378 | 10.783291 | 0.818420 | 65.199997 | 0.762252 | -0.072554 | NaN | 0.705040 | 0.312949 |
| 1476 | Saudi Arabia | 2015 | 6.345492 | 10.797967 | 0.819750 | 65.400002 | 0.820207 | -0.044803 | NaN | 0.723608 | 0.327139 |
| 1477 | Saudi Arabia | 2016 | 6.473921 | 10.791937 | 0.889932 | 65.699997 | 0.774268 | -0.132316 | NaN | 0.792999 | 0.266293 |
| 1478 | Saudi Arabia | 2017 | 6.294282 | 10.764459 | 0.840086 | 66.000000 | 0.814142 | -0.131142 | NaN | 0.774876 | 0.305842 |
| 1479 | Saudi Arabia | 2018 | 6.356393 | 10.770519 | 0.867848 | 66.300003 | 0.854922 | -0.192266 | NaN | 0.764405 | 0.288380 |
| 1480 | Saudi Arabia | 2019 | 6.561247 | 10.757097 | 0.911718 | 66.599998 | 0.891087 | -0.146843 | NaN | 0.731764 | 0.237737 |
| 1481 | Saudi Arabia | 2020 | 6.559588 | 10.700663 | 0.890256 | 66.900002 | 0.884220 | -0.110532 | NaN | 0.753608 | 0.251199 |
| 1482 | Senegal | 2006 | 4.417353 | 7.880945 | 0.760252 | 53.380001 | 0.735724 | -0.050643 | 0.805329 | 0.739953 | 0.224990 |
| 1483 | Senegal | 2007 | 4.679987 | 7.902722 | 0.718461 | 54.060001 | 0.698005 | -0.002132 | 0.826684 | 0.714047 | 0.198742 |
| 1484 | Senegal | 2008 | 4.683500 | 7.915670 | 0.756299 | 54.740002 | 0.611876 | -0.030309 | 0.879248 | 0.672881 | 0.252161 |
| 1485 | Senegal | 2009 | 4.335114 | 7.909231 | 0.810355 | 55.419998 | 0.556838 | -0.036257 | 0.918035 | 0.757378 | 0.227580 |
| 1486 | Senegal | 2010 | 4.372156 | 7.916806 | 0.760294 | 56.099998 | 0.777263 | -0.077270 | 0.850535 | 0.768812 | 0.142738 |
| 1487 | Senegal | 2011 | 3.834202 | 7.903617 | 0.602409 | 56.560001 | 0.640890 | -0.160456 | 0.869894 | 0.751883 | 0.180027 |
| 1488 | Senegal | 2012 | 3.668737 | 7.925668 | 0.711077 | 57.020000 | 0.668252 | -0.035587 | 0.851880 | 0.770918 | 0.213603 |
| 1489 | Senegal | 2013 | 3.647367 | 7.925508 | 0.822958 | 57.480000 | 0.635540 | -0.051867 | 0.836612 | 0.680121 | 0.165079 |
| 1490 | Senegal | 2014 | 4.394777 | 7.961481 | 0.855522 | 57.939999 | 0.692353 | -0.045290 | 0.699660 | 0.724697 | 0.157227 |
| 1491 | Senegal | 2015 | 4.617001 | 7.995122 | 0.701535 | 58.400002 | 0.719533 | -0.111103 | 0.765490 | 0.711035 | 0.207668 |
| 1492 | Senegal | 2016 | 4.594534 | 8.028671 | 0.838994 | 58.799999 | 0.743730 | -0.085590 | 0.794354 | 0.783818 | 0.244852 |
| 1493 | Senegal | 2017 | 4.683025 | 8.072124 | 0.743759 | 59.200001 | 0.686937 | -0.043522 | 0.825242 | 0.745732 | 0.290836 |
| 1494 | Senegal | 2018 | 4.769377 | 8.106148 | 0.739355 | 59.599998 | 0.629223 | -0.073627 | 0.804779 | 0.713894 | 0.247075 |
| 1495 | Senegal | 2019 | 5.488737 | 8.130020 | 0.687614 | 60.000000 | 0.758842 | -0.018804 | 0.795673 | 0.788973 | 0.331926 |
| 1496 | Serbia | 2007 | 4.750384 | 9.531929 | 0.844413 | 65.599998 | 0.452781 | -0.165310 | 0.904950 | 0.576048 | 0.334420 |
| 1497 | Serbia | 2009 | 4.380312 | 9.567513 | 0.770126 | 66.000000 | 0.372881 | -0.177623 | 0.960978 | 0.543799 | 0.435474 |
| 1498 | Serbia | 2010 | 4.461304 | 9.578816 | 0.725563 | 66.199997 | 0.462647 | -0.170204 | 0.965472 | 0.532202 | 0.415409 |
| 1499 | Serbia | 2011 | 4.815187 | 9.606869 | 0.773211 | 66.360001 | 0.440458 | -0.184845 | 0.976917 | 0.545481 | 0.410255 |
| 1500 | Serbia | 2012 | 5.154522 | 9.604883 | 0.819430 | 66.519997 | 0.460575 | -0.130401 | 0.951668 | 0.514332 | 0.371236 |
| 1501 | Serbia | 2013 | 5.101840 | 9.638266 | 0.828069 | 66.680000 | 0.532840 | -0.099876 | 0.908122 | 0.529108 | 0.403453 |
| 1502 | Serbia | 2014 | 5.112729 | 9.626937 | 0.782709 | 66.839996 | 0.531597 | 0.071945 | 0.911732 | 0.497755 | 0.326118 |
| 1503 | Serbia | 2015 | 5.317685 | 9.649492 | 0.816251 | 67.000000 | 0.545892 | -0.062090 | 0.859358 | 0.496241 | 0.302544 |
| 1504 | Serbia | 2016 | 5.752755 | 9.687587 | 0.894895 | 67.400002 | 0.614371 | -0.067876 | 0.889765 | 0.534827 | 0.298127 |
| 1505 | Serbia | 2017 | 5.122031 | 9.713195 | 0.883770 | 67.800003 | 0.684846 | -0.077480 | 0.851458 | 0.509721 | 0.326407 |
| 1506 | Serbia | 2018 | 5.936493 | 9.761643 | 0.852945 | 68.199997 | 0.739892 | -0.099542 | 0.863724 | 0.558941 | 0.296296 |
| 1507 | Serbia | 2019 | 6.241407 | 9.808065 | 0.903294 | 68.599998 | 0.752505 | -0.039932 | 0.813142 | 0.509102 | 0.242130 |
| 1508 | Serbia | 2020 | 6.041546 | 9.788260 | 0.852102 | 69.000000 | 0.843480 | 0.149401 | 0.824472 | 0.602846 | 0.357580 |
| 1509 | Sierra Leone | 2006 | 3.628185 | 7.136178 | 0.561356 | 40.299999 | 0.679001 | 0.100581 | 0.836166 | 0.505072 | 0.380655 |
| 1510 | Sierra Leone | 2007 | 3.585127 | 7.186534 | 0.686471 | 41.200001 | 0.720373 | 0.247709 | 0.830483 | 0.581781 | 0.289842 |
| 1511 | Sierra Leone | 2008 | 2.997251 | 7.215358 | 0.590737 | 42.099998 | 0.716396 | 0.148013 | 0.924901 | 0.533604 | 0.369601 |
| 1512 | Sierra Leone | 2010 | 4.133956 | 7.253870 | 0.811873 | 43.900002 | 0.726269 | 0.011958 | 0.910441 | 0.513532 | 0.290469 |
| 1513 | Sierra Leone | 2011 | 4.501644 | 7.292360 | 0.781581 | 44.320000 | 0.769738 | 0.004522 | 0.854647 | 0.445804 | 0.299528 |
| 1514 | Sierra Leone | 2013 | 4.514291 | 7.577167 | 0.708427 | 45.160000 | 0.719511 | -0.071460 | 0.855863 | 0.520902 | 0.422833 |
| 1515 | Sierra Leone | 2014 | 4.499970 | 7.599658 | 0.868556 | 45.580002 | 0.681498 | 0.033515 | 0.786132 | 0.570267 | 0.334213 |
| 1516 | Sierra Leone | 2015 | 4.908618 | 7.347185 | 0.610594 | 46.000000 | 0.624296 | 0.050446 | 0.824828 | 0.625106 | 0.414426 |
| 1517 | Sierra Leone | 2016 | 4.732953 | 7.384333 | 0.656723 | 47.599998 | 0.681202 | 0.106073 | 0.863265 | 0.583939 | 0.456181 |
| 1518 | Sierra Leone | 2017 | 4.089562 | 7.404040 | 0.652287 | 49.200001 | 0.710614 | 0.079156 | 0.848398 | 0.600368 | 0.495040 |
| 1519 | Sierra Leone | 2018 | 4.305683 | 7.416554 | 0.649638 | 50.799999 | 0.716484 | 0.095275 | 0.855733 | 0.551628 | 0.466267 |
| 1520 | Sierra Leone | 2019 | 3.447381 | 7.449132 | 0.610780 | 52.400002 | 0.717770 | 0.074056 | 0.873861 | 0.513375 | 0.438134 |
| 1521 | Singapore | 2006 | 6.462703 | 11.167536 | 0.904329 | 73.599998 | 0.756874 | 0.138254 | NaN | 0.750798 | 0.266721 |
| 1522 | Singapore | 2007 | 6.833755 | 11.212256 | 0.920632 | 73.900002 | 0.866892 | 0.293302 | 0.063615 | 0.700188 | 0.114407 |
| 1523 | Singapore | 2008 | 6.641957 | 11.177551 | 0.845259 | 74.199997 | 0.660659 | 0.045723 | 0.065775 | 0.720842 | 0.256087 |
| 1524 | Singapore | 2009 | 6.144677 | 11.148601 | 0.866255 | 74.500000 | 0.776382 | -0.074926 | 0.035198 | 0.499599 | 0.207548 |
| 1525 | Singapore | 2010 | 6.531402 | 11.266511 | 0.864162 | 74.800003 | 0.846185 | -0.018003 | 0.060282 | 0.602476 | 0.131343 |
| 1526 | Singapore | 2011 | 6.561042 | 11.307114 | 0.904474 | 75.019997 | 0.821816 | -0.148674 | 0.098924 | 0.482754 | 0.143629 |
| 1527 | Singapore | 2013 | 6.533207 | 11.357275 | 0.807911 | 75.459999 | 0.827103 | 0.114949 | 0.242398 | 0.769633 | 0.147688 |
| 1528 | Singapore | 2014 | 7.062365 | 11.382915 | 0.822033 | 75.680000 | 0.834888 | 0.154080 | 0.132603 | 0.841018 | 0.180233 |
| 1529 | Singapore | 2015 | 6.619525 | 11.400499 | 0.866437 | 75.900002 | 0.886891 | 0.149670 | 0.098944 | 0.803124 | 0.141585 |
| 1530 | Singapore | 2016 | 6.033481 | 11.419444 | 0.925128 | 76.199997 | 0.903736 | 0.142908 | 0.047311 | 0.823989 | 0.110942 |
| 1531 | Singapore | 2017 | 6.378438 | 11.461011 | 0.897350 | 76.500000 | 0.926128 | 0.135582 | 0.161791 | 0.800114 | 0.179325 |
| 1532 | Singapore | 2018 | 6.374564 | 11.490117 | 0.902841 | 76.800003 | 0.916078 | -0.065856 | 0.096563 | 0.787093 | 0.106871 |
| 1533 | Singapore | 2019 | 6.378360 | 11.485980 | 0.924918 | 77.099998 | 0.938042 | 0.027230 | 0.069620 | 0.722598 | 0.138069 |
| 1534 | Slovakia | 2006 | 5.264677 | 10.015392 | 0.953579 | 66.000000 | 0.542480 | -0.049709 | 0.945731 | 0.678114 | 0.307859 |
| 1535 | Slovakia | 2010 | 6.052223 | 10.168606 | 0.919640 | 66.800003 | 0.635758 | -0.101165 | 0.907136 | 0.666458 | 0.277207 |
| 1536 | Slovakia | 2011 | 5.945048 | 10.195559 | 0.917293 | 67.040001 | 0.727163 | 0.010069 | 0.907132 | 0.636583 | 0.287410 |
| 1537 | Slovakia | 2012 | 5.911059 | 10.212638 | 0.925751 | 67.279999 | 0.620004 | -0.028052 | 0.906532 | 0.656188 | 0.302261 |
| 1538 | Slovakia | 2013 | 5.936527 | 10.218249 | 0.909379 | 67.519997 | 0.597936 | -0.050910 | 0.914540 | 0.697576 | 0.276510 |
| 1539 | Slovakia | 2014 | 6.138873 | 10.244431 | 0.924243 | 67.760002 | 0.634792 | -0.125638 | 0.913870 | 0.703485 | 0.266785 |
| 1540 | Slovakia | 2015 | 6.162004 | 10.290573 | 0.943454 | 68.000000 | 0.587158 | -0.127852 | 0.927545 | 0.713708 | 0.269246 |
| 1541 | Slovakia | 2016 | 5.993163 | 10.310295 | 0.945179 | 68.300003 | 0.700099 | -0.060632 | 0.916609 | 0.774416 | 0.232092 |
| 1542 | Slovakia | 2017 | 6.365509 | 10.338752 | 0.913387 | 68.599998 | 0.714225 | -0.054508 | 0.920423 | 0.788020 | 0.212722 |
| 1543 | Slovakia | 2018 | 6.235111 | 10.375594 | 0.922379 | 68.900002 | 0.757634 | -0.167398 | 0.909945 | 0.754105 | 0.253190 |
| 1544 | Slovakia | 2019 | 6.243429 | 10.397957 | 0.933088 | 69.199997 | 0.771122 | -0.129015 | 0.925847 | 0.750380 | 0.251806 |
| 1545 | Slovakia | 2020 | 6.519098 | 10.331512 | 0.954160 | 69.500000 | 0.761897 | -0.074874 | 0.900534 | 0.763583 | 0.274448 |
| 1546 | Slovenia | 2006 | 5.811265 | 10.402996 | 0.936075 | 68.000000 | 0.935824 | 0.042652 | 0.707798 | 0.652222 | 0.307205 |
| 1547 | Slovenia | 2009 | 5.830161 | 10.410269 | 0.918697 | 68.900002 | 0.895957 | -0.018933 | 0.803634 | 0.640713 | 0.303117 |
| 1548 | Slovenia | 2010 | 6.082555 | 10.419256 | 0.917203 | 69.199997 | 0.895522 | 0.029250 | 0.844791 | 0.670814 | 0.295366 |
| 1549 | Slovenia | 2011 | 6.035964 | 10.425755 | 0.931166 | 69.400002 | 0.907441 | -0.025104 | 0.893134 | 0.651521 | 0.285321 |
| 1550 | Slovenia | 2012 | 6.062891 | 10.396906 | 0.924754 | 69.599998 | 0.904386 | -0.019661 | 0.890754 | 0.656376 | 0.283990 |
| 1551 | Slovenia | 2013 | 5.974889 | 10.385202 | 0.932120 | 69.800003 | 0.890060 | 0.035709 | 0.917840 | 0.635100 | 0.274269 |
| 1552 | Slovenia | 2014 | 5.678395 | 10.411524 | 0.908348 | 70.000000 | 0.887748 | 0.052348 | 0.909118 | 0.619818 | 0.290812 |
| 1553 | Slovenia | 2015 | 5.740642 | 10.432632 | 0.901164 | 70.199997 | 0.896007 | 0.007825 | 0.892198 | 0.659085 | 0.261419 |
| 1554 | Slovenia | 2016 | 5.936821 | 10.462640 | 0.934487 | 70.500000 | 0.903551 | -0.054714 | 0.838474 | 0.626206 | 0.271624 |
| 1555 | Slovenia | 2017 | 6.166838 | 10.509191 | 0.928188 | 70.800003 | 0.920863 | -0.025006 | 0.828795 | 0.615110 | 0.285601 |
| 1556 | Slovenia | 2018 | 6.249419 | 10.545921 | 0.940971 | 71.099998 | 0.942046 | -0.118911 | 0.839253 | 0.643972 | 0.275485 |
| 1557 | Slovenia | 2019 | 6.665274 | 10.563305 | 0.949402 | 71.400002 | 0.945431 | -0.101692 | 0.785442 | 0.678695 | 0.227838 |
| 1558 | Slovenia | 2020 | 6.462076 | 10.477870 | 0.953438 | 71.699997 | 0.958443 | -0.081357 | 0.796557 | 0.609949 | 0.313853 |
| 1559 | Somalia | 2014 | 5.528273 | NaN | 0.610836 | 49.599998 | 0.873879 | NaN | 0.456470 | 0.834454 | 0.207215 |
| 1560 | Somalia | 2015 | 5.353645 | NaN | 0.599281 | 50.099998 | 0.967869 | NaN | 0.410236 | 0.900668 | 0.186736 |
| 1561 | Somalia | 2016 | 4.667941 | NaN | 0.594417 | 50.000000 | 0.917323 | NaN | 0.440802 | 0.891423 | 0.193282 |
| 1562 | Somaliland region | 2009 | 4.991400 | NaN | 0.879567 | NaN | 0.746304 | NaN | 0.513372 | 0.818879 | 0.112012 |
| 1563 | Somaliland region | 2010 | 4.657363 | NaN | 0.829005 | NaN | 0.820182 | NaN | 0.471094 | 0.769375 | 0.083426 |
| 1564 | Somaliland region | 2011 | 4.930572 | NaN | 0.787962 | NaN | 0.858104 | NaN | 0.357341 | 0.748686 | 0.122244 |
| 1565 | Somaliland region | 2012 | 5.057314 | NaN | 0.786291 | NaN | 0.758219 | NaN | 0.333832 | 0.735189 | 0.152428 |
| 1566 | South Africa | 2006 | 5.083987 | 9.386314 | 0.913030 | 48.020000 | 0.648763 | -0.083790 | NaN | 0.802440 | 0.222731 |
| 1567 | South Africa | 2007 | 5.204454 | 9.425617 | 0.788308 | 48.639999 | 0.689988 | -0.157790 | 0.858651 | 0.735380 | 0.210185 |
| 1568 | South Africa | 2008 | 5.346307 | 9.443687 | 0.809542 | 49.259998 | 0.748846 | -0.095482 | 0.865791 | 0.772835 | 0.206243 |
| 1569 | South Africa | 2009 | 5.218431 | 9.414272 | 0.877359 | 49.880001 | 0.739410 | -0.153862 | 0.904342 | 0.727469 | 0.230896 |
| 1570 | South Africa | 2010 | 4.652429 | 9.429664 | 0.917056 | 50.500000 | 0.738906 | -0.202231 | 0.790629 | 0.793740 | 0.123753 |
| 1571 | South Africa | 2011 | 4.930511 | 9.446725 | 0.857703 | 51.459999 | 0.835448 | -0.154246 | 0.819182 | 0.763071 | 0.230214 |
| 1572 | South Africa | 2012 | 5.133888 | 9.452785 | 0.906595 | 52.419998 | 0.590145 | -0.162909 | 0.838217 | 0.761367 | 0.178183 |
| 1573 | South Africa | 2013 | 3.660727 | 9.461276 | 0.839424 | 53.380001 | 0.714169 | -0.076853 | 0.799543 | 0.772518 | 0.166549 |
| 1574 | South Africa | 2014 | 4.828456 | 9.463746 | 0.881152 | 54.340000 | 0.794031 | -0.116906 | 0.820258 | 0.797624 | 0.243358 |
| 1575 | South Africa | 2015 | 4.887326 | 9.460323 | 0.898096 | 55.299999 | 0.862449 | -0.127049 | 0.852695 | 0.780759 | 0.160788 |
| 1576 | South Africa | 2016 | 4.769740 | 9.449658 | 0.875390 | 55.700001 | 0.774136 | -0.070200 | 0.812859 | 0.785724 | 0.301328 |
| 1577 | South Africa | 2017 | 4.513655 | 9.449627 | 0.870313 | 56.099998 | 0.787428 | -0.128618 | 0.864782 | 0.784801 | 0.268175 |
| 1578 | South Africa | 2018 | 4.883922 | 9.443890 | 0.841344 | 56.500000 | 0.752731 | -0.050273 | 0.841193 | 0.812167 | 0.282708 |
| 1579 | South Africa | 2019 | 5.034863 | 9.432028 | 0.847720 | 56.900002 | 0.738339 | -0.133970 | 0.819824 | 0.800584 | 0.268456 |
| 1580 | South Africa | 2020 | 4.946801 | 9.332463 | 0.891050 | 57.299999 | 0.756946 | -0.014951 | 0.912407 | 0.820338 | 0.294276 |
| 1581 | South Korea | 2006 | 5.332178 | 10.309702 | 0.775499 | 70.199997 | 0.715242 | -0.052023 | 0.798615 | 0.650549 | 0.338152 |
| 1582 | South Korea | 2007 | 5.767276 | 10.361026 | 0.826712 | 70.500000 | 0.655828 | -0.059288 | 0.802753 | 0.689788 | 0.226402 |
| 1583 | South Korea | 2008 | 5.389625 | 10.383118 | 0.753610 | 70.800003 | 0.523679 | -0.102214 | 0.770960 | 0.642739 | 0.239057 |
| 1584 | South Korea | 2009 | 5.647690 | 10.385866 | 0.810903 | 71.099998 | 0.600166 | -0.095942 | 0.787497 | 0.697018 | 0.208521 |
| 1585 | South Korea | 2010 | 6.116024 | 10.446717 | 0.815517 | 71.400002 | 0.676653 | -0.033234 | 0.751621 | 0.661971 | 0.130337 |
| 1586 | South Korea | 2011 | 6.946599 | 10.475221 | 0.809104 | 71.660004 | 0.682356 | -0.048490 | 0.827301 | 0.655812 | 0.167833 |
| 1587 | South Korea | 2012 | 6.003287 | 10.493705 | 0.775397 | 71.919998 | 0.618398 | NaN | 0.843719 | 0.663815 | 0.206365 |
| 1588 | South Korea | 2013 | 5.958810 | 10.520309 | 0.796694 | 72.180000 | 0.641884 | -0.049806 | 0.831863 | 0.676295 | 0.188766 |
| 1589 | South Korea | 2014 | 5.801325 | 10.545550 | 0.737754 | 72.440002 | 0.623194 | -0.042916 | 0.834068 | 0.652949 | 0.282808 |
| 1590 | South Korea | 2015 | 5.780211 | 10.567981 | 0.768351 | 72.699997 | 0.615849 | -0.035574 | 0.840722 | 0.649948 | 0.244324 |
| 1591 | South Korea | 2016 | 5.970564 | 10.593056 | 0.811163 | 73.000000 | 0.590956 | 0.026376 | 0.861816 | 0.676223 | 0.232733 |
| 1592 | South Korea | 2017 | 5.873887 | 10.621353 | 0.806930 | 73.300003 | 0.538114 | 0.014370 | 0.850690 | 0.623378 | 0.234826 |
| 1593 | South Korea | 2018 | 5.840231 | 10.642900 | 0.797724 | 73.599998 | 0.600162 | -0.088885 | 0.796826 | 0.661209 | 0.217146 |
| 1594 | South Korea | 2019 | 5.902817 | 10.661044 | 0.783161 | 73.900002 | 0.706032 | -0.055295 | 0.717696 | 0.684407 | 0.235967 |
| 1595 | South Korea | 2020 | 5.792696 | 10.648074 | 0.807952 | 74.199997 | 0.711480 | -0.105868 | 0.664694 | 0.639556 | 0.247060 |
| 1596 | South Sudan | 2014 | 3.831992 | NaN | 0.545118 | 49.840000 | 0.567259 | NaN | 0.741541 | 0.614024 | 0.428320 |
| 1597 | South Sudan | 2015 | 4.070771 | NaN | 0.584781 | 50.200001 | 0.511631 | NaN | 0.709606 | 0.586278 | 0.449795 |
| 1598 | South Sudan | 2016 | 2.888112 | NaN | 0.532152 | 50.599998 | 0.439919 | NaN | 0.785318 | 0.614771 | 0.549257 |
| 1599 | South Sudan | 2017 | 2.816622 | NaN | 0.556823 | 51.000000 | 0.456011 | NaN | 0.761270 | 0.585602 | 0.517364 |
| 1600 | Spain | 2005 | 7.152786 | 10.546350 | 0.961043 | 71.500000 | 0.916165 | NaN | 0.777272 | 0.775784 | 0.240643 |
| 1601 | Spain | 2007 | 6.994615 | 10.586556 | 0.956859 | 72.059998 | 0.782082 | -0.093424 | 0.783718 | 0.763125 | 0.263593 |
| 1602 | Spain | 2008 | 7.294473 | 10.579435 | 0.948270 | 72.339996 | 0.833786 | -0.149568 | 0.683210 | 0.772095 | 0.259691 |
| 1603 | Spain | 2009 | 6.198601 | 10.532220 | 0.929454 | 72.620003 | 0.748515 | -0.127339 | 0.797705 | 0.752165 | 0.335877 |
| 1604 | Spain | 2010 | 6.188262 | 10.529244 | 0.949940 | 72.900002 | 0.796496 | -0.137998 | 0.839746 | 0.724312 | 0.321819 |
| 1605 | Spain | 2011 | 6.518249 | 10.517514 | 0.944444 | 73.019997 | 0.818651 | -0.121754 | 0.845543 | 0.737269 | 0.356102 |
| 1606 | Spain | 2012 | 6.290690 | 10.486824 | 0.937023 | 73.139999 | 0.754586 | -0.059431 | 0.843593 | 0.749277 | 0.366474 |
| 1607 | Spain | 2013 | 6.150027 | 10.475642 | 0.928640 | 73.260002 | 0.759356 | -0.101454 | 0.915823 | 0.696296 | 0.371839 |
| 1608 | Spain | 2014 | 6.456478 | 10.492376 | 0.947864 | 73.379997 | 0.738472 | -0.028166 | 0.853888 | 0.716266 | 0.335460 |
| 1609 | Spain | 2015 | 6.380663 | 10.530787 | 0.956472 | 73.500000 | 0.732000 | -0.072339 | 0.821665 | 0.732269 | 0.284694 |
| 1610 | Spain | 2016 | 6.318612 | 10.559805 | 0.941737 | 73.800003 | 0.768174 | -0.048091 | 0.818559 | 0.652816 | 0.300829 |
| 1611 | Spain | 2017 | 6.230173 | 10.585966 | 0.903158 | 74.099998 | 0.755561 | -0.032063 | 0.791269 | 0.625056 | 0.302388 |
| 1612 | Spain | 2018 | 6.513371 | 10.604824 | 0.910315 | 74.400002 | 0.722251 | -0.074976 | 0.776504 | 0.659188 | 0.357191 |
| 1613 | Spain | 2019 | 6.457449 | 10.618478 | 0.949013 | 74.699997 | 0.777967 | -0.048639 | 0.730338 | 0.663313 | 0.315518 |
| 1614 | Spain | 2020 | 6.502175 | 10.488059 | 0.934935 | 75.000000 | 0.783257 | -0.120613 | 0.729977 | 0.686178 | 0.316617 |
| 1615 | Sri Lanka | 2006 | 4.344611 | 8.911856 | 0.863599 | 65.779999 | 0.723848 | 0.062403 | 0.837785 | 0.756676 | 0.216330 |
| 1616 | Sri Lanka | 2007 | 4.414805 | 8.970224 | 0.838327 | 65.860001 | 0.735853 | 0.109853 | 0.846718 | 0.708772 | 0.219856 |
| 1617 | Sri Lanka | 2008 | 4.430846 | 9.020894 | 0.815703 | 65.940002 | 0.833836 | 0.162589 | 0.861397 | 0.789877 | 0.152588 |
| 1618 | Sri Lanka | 2009 | 4.212027 | 9.048715 | 0.829612 | 66.019997 | 0.798871 | 0.306048 | 0.689926 | 0.769714 | 0.172401 |
| 1619 | Sri Lanka | 2010 | 3.976905 | 9.118978 | 0.814367 | 66.099998 | 0.738209 | 0.258537 | 0.769478 | 0.822605 | 0.163472 |
| 1620 | Sri Lanka | 2011 | 4.180569 | 9.192944 | 0.841938 | 66.199997 | 0.822637 | 0.144856 | 0.760301 | 0.824981 | 0.174927 |
| 1621 | Sri Lanka | 2012 | 4.224593 | 9.279157 | 0.824357 | 66.300003 | 0.800397 | 0.160591 | 0.822879 | 0.863880 | 0.196871 |
| 1622 | Sri Lanka | 2013 | 4.364694 | 9.304748 | 0.809175 | 66.400002 | 0.834020 | 0.268219 | 0.842014 | 0.860365 | 0.208130 |
| 1623 | Sri Lanka | 2014 | 4.267933 | 9.343831 | 0.804798 | 66.500000 | 0.867936 | 0.299043 | 0.790627 | 0.842815 | 0.186896 |
| 1624 | Sri Lanka | 2015 | 4.611607 | 9.383496 | 0.862500 | 66.599998 | 0.902075 | 0.319147 | 0.859471 | 0.848233 | 0.234751 |
| 1625 | Sri Lanka | 2017 | 4.330945 | 9.440189 | 0.822771 | 67.000000 | 0.827077 | 0.093778 | 0.844210 | 0.794952 | 0.269728 |
| 1626 | Sri Lanka | 2018 | 4.435024 | 9.462235 | 0.832882 | 67.199997 | 0.858874 | 0.106040 | 0.855908 | 0.830616 | 0.301814 |
| 1627 | Sri Lanka | 2019 | 4.213299 | 9.478694 | 0.814939 | 67.400002 | 0.824277 | 0.051187 | 0.863342 | 0.816390 | 0.314543 |
| 1628 | Sudan | 2009 | 4.454917 | 8.105703 | 0.911407 | 53.700001 | 0.709979 | 0.076804 | 0.701229 | 0.733572 | 0.244927 |
| 1629 | Sudan | 2010 | 4.435160 | 8.076443 | 0.854824 | 54.000000 | 0.648155 | -0.040054 | 0.736897 | 0.668583 | 0.220789 |
| 1630 | Sudan | 2011 | 4.314456 | 8.203635 | 0.817786 | 54.279999 | 0.582539 | -0.024156 | 0.662519 | 0.585826 | 0.248501 |
| 1631 | Sudan | 2012 | 4.550499 | 8.295729 | 0.812501 | 54.560001 | 0.411948 | -0.055609 | 0.733679 | 0.576178 | 0.242374 |
| 1632 | Sudan | 2014 | 4.138673 | 8.317068 | 0.810616 | 55.119999 | 0.390096 | -0.063395 | 0.793785 | 0.540845 | 0.302725 |
| 1633 | Suriname | 2012 | 6.269287 | 9.797085 | 0.797262 | 62.240002 | 0.885488 | -0.077173 | 0.751283 | 0.764223 | 0.250365 |
| 1634 | Swaziland | 2011 | 4.867091 | 8.940104 | 0.837150 | 40.808292 | 0.607157 | -0.066733 | 0.917250 | 0.820613 | 0.251053 |
| 1635 | Swaziland | 2018 | 4.211565 | 9.060224 | 0.779270 | 50.353203 | 0.709974 | -0.178416 | 0.692341 | 0.824355 | 0.252339 |
| 1636 | Swaziland | 2019 | 4.396115 | 9.069710 | 0.759098 | 51.270393 | 0.596682 | -0.190738 | 0.723508 | 0.777627 | 0.279595 |
| 1637 | Sweden | 2005 | 7.376316 | 10.739267 | 0.951470 | 71.199997 | 0.964395 | NaN | NaN | 0.839870 | 0.150766 |
| 1638 | Sweden | 2007 | 7.241363 | 10.805614 | 0.916559 | 71.480003 | 0.909962 | 0.146358 | 0.289332 | 0.796209 | 0.177412 |
| 1639 | Sweden | 2008 | 7.515997 | 10.793308 | 0.923092 | 71.620003 | 0.911609 | 0.125246 | 0.313961 | 0.804467 | 0.134403 |
| 1640 | Sweden | 2009 | 7.265977 | 10.740421 | 0.902533 | 71.760002 | 0.864005 | 0.220528 | 0.292112 | 0.819678 | 0.151363 |
| 1641 | Sweden | 2010 | 7.496019 | 10.789714 | 0.970243 | 71.900002 | 0.904700 | 0.141384 | 0.253087 | 0.833033 | 0.200112 |
| 1642 | Sweden | 2011 | 7.382232 | 10.813616 | 0.920521 | 71.980003 | 0.941115 | 0.161460 | 0.268513 | 0.814561 | 0.179152 |
| 1643 | Sweden | 2012 | 7.560148 | 10.800318 | 0.929397 | 72.059998 | 0.944382 | 0.131922 | 0.253543 | 0.855100 | 0.170226 |
| 1644 | Sweden | 2013 | 7.434011 | 10.803652 | 0.915648 | 72.139999 | 0.935911 | 0.158880 | 0.324482 | 0.829284 | 0.184420 |
| 1645 | Sweden | 2014 | 7.239148 | 10.819961 | 0.932720 | 72.220001 | 0.945273 | 0.201714 | 0.250390 | 0.835672 | 0.207688 |
| 1646 | Sweden | 2015 | 7.288922 | 10.853300 | 0.929460 | 72.300003 | 0.935072 | 0.211176 | 0.231964 | 0.817942 | 0.190992 |
| 1647 | Sweden | 2016 | 7.368744 | 10.861230 | 0.912061 | 72.400002 | 0.918036 | 0.145734 | 0.246182 | 0.815695 | 0.200607 |
| 1648 | Sweden | 2017 | 7.286805 | 10.873111 | 0.914017 | 72.500000 | 0.934582 | 0.170274 | 0.239367 | 0.813548 | 0.175067 |
| 1649 | Sweden | 2018 | 7.374792 | 10.880807 | 0.930680 | 72.599998 | 0.941725 | 0.076688 | 0.262797 | 0.822676 | 0.160755 |
| 1650 | Sweden | 2019 | 7.398093 | 10.881908 | 0.933645 | 72.699997 | 0.941515 | 0.091022 | 0.250088 | 0.826284 | 0.202000 |
| 1651 | Sweden | 2020 | 7.314341 | 10.837904 | 0.935582 | 72.800003 | 0.951182 | 0.090818 | 0.203440 | 0.766376 | 0.221933 |
| 1652 | Switzerland | 2006 | 7.473253 | 11.049914 | 0.951352 | 71.540001 | 0.918958 | 0.290456 | 0.407931 | 0.821402 | 0.211929 |
| 1653 | Switzerland | 2009 | 7.524521 | 11.054919 | 0.938339 | 72.260002 | 0.891277 | 0.125042 | 0.342427 | 0.814037 | 0.201585 |
| 1654 | Switzerland | 2012 | 7.776209 | 11.079147 | 0.946864 | 72.779999 | 0.945428 | 0.138619 | 0.323241 | 0.859107 | 0.176007 |
| 1655 | Switzerland | 2014 | 7.492804 | 11.097996 | 0.958796 | 73.059998 | 0.949401 | 0.060122 | 0.283090 | 0.822913 | 0.188794 |
| 1656 | Switzerland | 2015 | 7.572137 | 11.099858 | 0.938334 | 73.199997 | 0.927802 | 0.108924 | 0.209534 | 0.808529 | 0.165759 |
| 1657 | Switzerland | 2016 | 7.458520 | 11.106019 | 0.927628 | 73.500000 | 0.933947 | 0.088443 | 0.301563 | 0.779471 | 0.206317 |
| 1658 | Switzerland | 2017 | 7.473593 | 11.114521 | 0.949661 | 73.800003 | 0.924997 | 0.179773 | 0.316183 | 0.773997 | 0.195871 |
| 1659 | Switzerland | 2018 | 7.508587 | 11.134289 | 0.930291 | 74.099998 | 0.926415 | 0.100956 | 0.301260 | 0.792226 | 0.191520 |
| 1660 | Switzerland | 2019 | 7.694221 | 11.136454 | 0.948513 | 74.400002 | 0.913167 | 0.036215 | 0.293701 | 0.797893 | 0.170762 |
| 1661 | Switzerland | 2020 | 7.508435 | 11.080893 | 0.946316 | 74.699997 | 0.917343 | -0.063502 | 0.280367 | 0.768705 | 0.193229 |
| 1662 | Syria | 2008 | 5.323332 | 8.651800 | 0.712370 | 63.900002 | 0.660753 | 0.121619 | 0.680204 | 0.609097 | 0.338427 |
| 1663 | Syria | 2009 | 4.978971 | 8.653676 | 0.842402 | 64.000000 | 0.748259 | 0.081666 | 0.687760 | 0.574330 | 0.292455 |
| 1664 | Syria | 2010 | 4.464708 | 8.729084 | 0.934232 | 64.099998 | 0.647048 | 0.007883 | 0.743094 | 0.557652 | 0.224644 |
| 1665 | Syria | 2011 | 4.037889 | 8.726923 | 0.575722 | 62.320000 | 0.530433 | 0.130682 | 0.740586 | 0.598737 | 0.495505 |
| 1666 | Syria | 2012 | 3.164491 | 8.562601 | 0.588395 | 60.540001 | 0.466771 | 0.315987 | 0.672964 | 0.464439 | 0.704590 |
| 1667 | Syria | 2013 | 2.687553 | 8.396470 | 0.585450 | 58.759998 | 0.454883 | 0.225454 | 0.663431 | 0.386987 | 0.622230 |
| 1668 | Syria | 2015 | 3.461913 | 8.441537 | 0.463913 | 55.200001 | 0.448271 | 0.044835 | 0.685237 | 0.369440 | 0.642589 |
| 1669 | Taiwan Province of China | 2006 | 6.189050 | 10.613232 | 0.882246 | 68.680000 | 0.629910 | -0.029827 | 0.845850 | 0.813638 | 0.094316 |
| 1670 | Taiwan Province of China | 2008 | 5.547682 | 10.606202 | 0.830005 | 69.139999 | 0.641715 | -0.016732 | 0.784832 | 0.794352 | 0.169157 |
| 1671 | Taiwan Province of China | 2010 | 6.228531 | 10.690681 | 0.831413 | 69.599998 | 0.676587 | 0.004753 | 0.821365 | 0.845345 | 0.135867 |
| 1672 | Taiwan Province of China | 2011 | 6.308915 | 10.705154 | 0.862521 | NaN | 0.761488 | 0.035270 | 0.754584 | 0.826713 | 0.112288 |
| 1673 | Taiwan Province of China | 2012 | 6.125917 | 10.715845 | 0.825072 | NaN | 0.698195 | 0.021749 | 0.802829 | 0.821362 | 0.140011 |
| 1674 | Taiwan Province of China | 2013 | 6.340344 | 10.750063 | 0.816993 | NaN | 0.690071 | 0.001518 | 0.841232 | 0.846232 | 0.124445 |
| 1675 | Taiwan Province of China | 2014 | 6.363497 | 10.797789 | 0.870012 | NaN | 0.692900 | 0.091989 | 0.865741 | 0.848841 | 0.108366 |
| 1676 | Taiwan Province of China | 2015 | 6.450088 | 10.842318 | 0.885389 | NaN | 0.700810 | 0.018658 | 0.857195 | 0.831987 | 0.129349 |
| 1677 | Taiwan Province of China | 2016 | 6.512851 | 10.854927 | 0.894989 | NaN | 0.718925 | -0.048804 | 0.810521 | 0.833153 | 0.108305 |
| 1678 | Taiwan Province of China | 2017 | 6.359451 | 10.870996 | 0.891119 | NaN | 0.759655 | -0.070494 | 0.742780 | 0.837277 | 0.114123 |
| 1679 | Taiwan Province of China | 2018 | 6.467005 | NaN | 0.896459 | NaN | 0.741033 | NaN | 0.735971 | 0.848399 | 0.092696 |
| 1680 | Taiwan Province of China | 2019 | 6.537090 | NaN | 0.893431 | NaN | 0.814484 | NaN | 0.718112 | 0.860071 | 0.093412 |
| 1681 | Taiwan Province of China | 2020 | 6.751068 | NaN | 0.900833 | NaN | 0.798835 | NaN | 0.710567 | 0.845393 | 0.082737 |
| 1682 | Tajikistan | 2006 | 4.613099 | 7.554471 | 0.723841 | 60.639999 | 0.701760 | -0.088468 | 0.768155 | 0.565764 | 0.194671 |
| 1683 | Tajikistan | 2007 | 4.431609 | 7.609175 | 0.726655 | 61.080002 | 0.818355 | 0.000432 | 0.658520 | 0.694193 | 0.133114 |
| 1684 | Tajikistan | 2008 | 5.063987 | 7.664672 | 0.700901 | 61.520000 | 0.815955 | 0.017623 | 0.723377 | 0.605863 | 0.160436 |
| 1685 | Tajikistan | 2009 | 4.575175 | 7.681615 | 0.675653 | 61.959999 | 0.743787 | 0.000688 | 0.791704 | 0.605244 | 0.203190 |
| 1686 | Tajikistan | 2010 | 4.380636 | 7.722940 | 0.759163 | 62.400002 | 0.784496 | 0.061829 | 0.678528 | 0.642683 | 0.191733 |
| 1687 | Tajikistan | 2011 | 4.262671 | 7.771989 | 0.750738 | 62.560001 | 0.776180 | -0.118868 | 0.672199 | 0.697810 | 0.165632 |
| 1688 | Tajikistan | 2012 | 4.496572 | 7.821405 | 0.728591 | 62.720001 | 0.749035 | -0.072731 | 0.717098 | 0.714460 | 0.198191 |
| 1689 | Tajikistan | 2013 | 4.966521 | 7.869584 | 0.700643 | 62.880001 | 0.693120 | 0.063402 | 0.764237 | 0.676519 | 0.169621 |
| 1690 | Tajikistan | 2014 | 4.896158 | 7.910819 | 0.809826 | 63.040001 | 0.852732 | 0.001544 | 0.698431 | 0.656047 | 0.196154 |
| 1691 | Tajikistan | 2015 | 5.124211 | 7.945079 | 0.843933 | 63.200001 | 0.846542 | 0.022057 | 0.741690 | 0.688922 | 0.195661 |
| 1692 | Tajikistan | 2016 | 5.103721 | 7.987065 | 0.856657 | 63.500000 | 0.703027 | 0.009666 | 0.631888 | 0.644485 | 0.219800 |
| 1693 | Tajikistan | 2017 | 5.829234 | 8.035774 | 0.662693 | 63.799999 | 0.832002 | 0.124276 | 0.718337 | 0.602668 | 0.277725 |
| 1694 | Tajikistan | 2018 | 5.497469 | 8.081698 | 0.875243 | 64.099998 | NaN | -0.064819 | 0.577946 | 0.694633 | 0.219794 |
| 1695 | Tajikistan | 2019 | 5.464015 | 8.125557 | 0.879823 | 64.400002 | NaN | -0.044561 | 0.490029 | 0.728972 | 0.178497 |
| 1696 | Tajikistan | 2020 | 5.373399 | 8.080357 | 0.789745 | 64.699997 | NaN | -0.040467 | 0.549786 | 0.748898 | 0.344161 |
| 1697 | Tanzania | 2006 | 3.922484 | 7.485086 | 0.782916 | 48.700001 | 0.786859 | -0.027226 | 0.649105 | 0.748167 | 0.209238 |
| 1698 | Tanzania | 2007 | 4.317950 | 7.522392 | 0.707852 | 49.599998 | 0.715832 | -0.012852 | 0.706752 | 0.755214 | 0.219853 |
| 1699 | Tanzania | 2008 | 4.384742 | 7.549336 | 0.774360 | 50.500000 | 0.562212 | 0.255817 | 0.930032 | 0.744346 | 0.178047 |
| 1700 | Tanzania | 2009 | 3.407508 | 7.572010 | 0.836828 | 51.400002 | 0.606549 | 0.308352 | 0.902627 | 0.778500 | 0.160527 |
| 1701 | Tanzania | 2010 | 3.229129 | 7.604382 | 0.812532 | 52.299999 | 0.597122 | 0.138955 | 0.866264 | 0.716567 | 0.146119 |
| 1702 | Tanzania | 2011 | 4.073562 | 7.648876 | 0.882530 | 53.040001 | 0.736030 | -0.046155 | 0.816376 | 0.764551 | 0.145141 |
| 1703 | Tanzania | 2012 | 4.006897 | 7.663198 | 0.832056 | 53.779999 | 0.577453 | 0.213284 | 0.886998 | 0.678828 | 0.195307 |
| 1704 | Tanzania | 2013 | 3.852395 | 7.698932 | 0.803419 | 54.520000 | 0.654182 | 0.054437 | 0.859006 | 0.737968 | 0.191288 |
| 1705 | Tanzania | 2014 | 3.483279 | 7.734119 | 0.789081 | 55.259998 | 0.654125 | 0.110466 | 0.877886 | 0.730893 | 0.241431 |
| 1706 | Tanzania | 2015 | 3.660597 | 7.763930 | 0.790263 | 56.000000 | 0.758685 | 0.148695 | 0.906423 | 0.619377 | 0.191748 |
| 1707 | Tanzania | 2016 | 2.902734 | 7.800395 | 0.637756 | 56.500000 | 0.775485 | 0.178778 | 0.739247 | 0.693552 | 0.245986 |
| 1708 | Tanzania | 2017 | 3.347121 | 7.836148 | 0.705010 | 57.000000 | 0.800496 | 0.115518 | 0.653606 | 0.714646 | 0.255336 |
| 1709 | Tanzania | 2018 | 3.445023 | 7.859404 | 0.675330 | 57.500000 | 0.807142 | 0.153193 | 0.611534 | 0.762089 | 0.221005 |
| 1710 | Tanzania | 2019 | 3.640155 | 7.886240 | 0.687268 | 58.000000 | 0.850133 | 0.100390 | 0.589294 | 0.726239 | 0.243098 |
| 1711 | Tanzania | 2020 | 3.785684 | 7.881270 | 0.739817 | 58.500000 | 0.830343 | 0.295272 | 0.520632 | 0.685533 | 0.271118 |
| 1712 | Thailand | 2006 | 5.885433 | 9.461148 | 0.894327 | 64.139999 | 0.863195 | 0.331460 | 0.934745 | 0.813509 | 0.164123 |
| 1713 | Thailand | 2007 | 5.783891 | 9.508475 | 0.888634 | 64.480003 | 0.870159 | 0.390946 | 0.897753 | 0.831810 | 0.180010 |
| 1714 | Thailand | 2008 | 5.636471 | 9.520327 | 0.831711 | 64.820000 | 0.867834 | 0.425482 | 0.933373 | 0.819038 | 0.145059 |
| 1715 | Thailand | 2009 | 5.475645 | 9.508361 | 0.893245 | 65.160004 | 0.868224 | 0.524908 | 0.903822 | 0.897641 | 0.166086 |
| 1716 | Thailand | 2010 | 6.216703 | 9.575911 | 0.897651 | 65.500000 | 0.859636 | 0.535985 | 0.916693 | 0.901268 | 0.181523 |
| 1717 | Thailand | 2011 | 6.663609 | 9.579475 | 0.884351 | 65.720001 | 0.926882 | 0.400159 | 0.923196 | 0.934374 | 0.116676 |
| 1718 | Thailand | 2012 | 6.300235 | 9.644709 | 0.906098 | 65.940002 | 0.846933 | 0.379859 | 0.908612 | 0.854544 | 0.137503 |
| 1719 | Thailand | 2013 | 6.231025 | 9.666691 | 0.926378 | 66.160004 | 0.781082 | 0.456227 | 0.925430 | 0.845981 | 0.140831 |
| 1720 | Thailand | 2014 | 6.985464 | 9.672178 | 0.933167 | 66.379997 | 0.899846 | 0.552521 | 0.919834 | 0.811370 | 0.168738 |
| 1721 | Thailand | 2015 | 6.201763 | 9.699015 | 0.866325 | 66.599998 | 0.884917 | 0.315948 | 0.913651 | 0.910497 | 0.174081 |
| 1722 | Thailand | 2016 | 6.073640 | 9.729001 | 0.907544 | 66.800003 | 0.924146 | 0.355719 | 0.877978 | 0.834758 | 0.217880 |
| 1723 | Thailand | 2017 | 5.938895 | 9.765407 | 0.877269 | 67.000000 | 0.922897 | 0.212491 | 0.883817 | 0.816322 | 0.231598 |
| 1724 | Thailand | 2018 | 6.011562 | 9.802921 | 0.873052 | 67.199997 | 0.904828 | 0.258844 | 0.906596 | 0.843489 | 0.198190 |
| 1725 | Thailand | 2019 | 6.022151 | 9.823529 | 0.903051 | 67.400002 | 0.898245 | 0.308830 | 0.877040 | 0.842873 | 0.208184 |
| 1726 | Thailand | 2020 | 5.884544 | 9.769243 | 0.866703 | 67.599998 | 0.840463 | 0.273056 | 0.918340 | 0.783270 | 0.326169 |
| 1727 | Togo | 2006 | 3.202429 | 7.077817 | 0.435414 | 49.259998 | 0.628228 | -0.006546 | 0.849972 | 0.614520 | 0.348205 |
| 1728 | Togo | 2008 | 2.807855 | 7.051686 | 0.291334 | 50.180000 | 0.286814 | -0.054630 | 0.931986 | 0.362498 | 0.378715 |
| 1729 | Togo | 2011 | 2.936221 | 7.145922 | 0.302955 | 51.580002 | 0.584088 | -0.069823 | 0.832004 | 0.480281 | 0.395363 |
| 1730 | Togo | 2014 | 2.838959 | 7.247175 | 0.444339 | 53.020000 | 0.663193 | -0.084710 | 0.795342 | 0.582750 | 0.442813 |
| 1731 | Togo | 2015 | 3.768302 | 7.277406 | 0.478593 | 53.500000 | 0.771577 | -0.068682 | 0.733262 | 0.598805 | 0.415781 |
| 1732 | Togo | 2016 | 3.878578 | 7.306319 | 0.509441 | 53.900002 | 0.730287 | -0.006936 | 0.815044 | 0.604244 | 0.482886 |
| 1733 | Togo | 2017 | 4.360805 | 7.324177 | 0.507805 | 54.299999 | 0.716694 | -0.042179 | 0.725520 | 0.614189 | 0.425824 |
| 1734 | Togo | 2018 | 4.022895 | 7.347652 | 0.596354 | 54.700001 | 0.611966 | -0.006869 | 0.808538 | 0.608449 | 0.446454 |
| 1735 | Togo | 2019 | 4.179494 | 7.375211 | 0.538702 | 55.099998 | 0.617420 | 0.064775 | 0.736675 | 0.590229 | 0.443870 |
| 1736 | Trinidad and Tobago | 2006 | 5.832189 | 10.223845 | 0.886789 | 61.759998 | 0.840089 | 0.141430 | 0.917428 | 0.797640 | 0.229044 |
| 1737 | Trinidad and Tobago | 2008 | 6.696444 | 10.294565 | 0.858300 | 62.080002 | 0.838140 | 0.086612 | 0.958828 | 0.817198 | 0.183790 |
| 1738 | Trinidad and Tobago | 2011 | 6.518746 | 10.262998 | 0.862839 | 62.540001 | 0.775392 | 0.077540 | 0.899957 | 0.906178 | 0.134091 |
| 1739 | Trinidad and Tobago | 2013 | 6.167707 | 10.284636 | 0.883180 | 62.820000 | 0.846941 | 0.127746 | 0.947674 | 0.832503 | 0.285929 |
| 1740 | Trinidad and Tobago | 2017 | 6.191860 | 10.182920 | 0.916029 | 63.500000 | 0.859140 | 0.014855 | 0.911336 | 0.846467 | 0.248099 |
| 1741 | Tunisia | 2009 | 5.025470 | 9.197462 | NaN | 64.959999 | 0.781496 | -0.118570 | 0.722211 | NaN | NaN |
| 1742 | Tunisia | 2010 | 5.130521 | 9.221612 | 0.863188 | 65.099998 | 0.623593 | -0.135169 | 0.732379 | 0.724581 | 0.248913 |
| 1743 | Tunisia | 2011 | 4.876482 | 9.192277 | 0.714891 | 65.279999 | 0.603124 | -0.198725 | 0.912657 | 0.587680 | 0.248197 |
| 1744 | Tunisia | 2012 | 4.463531 | 9.221737 | 0.614423 | 65.459999 | 0.567737 | -0.176225 | 0.899453 | 0.520914 | 0.327000 |
| 1745 | Tunisia | 2013 | 5.245605 | 9.240366 | 0.647967 | 65.639999 | 0.536288 | -0.206911 | 0.886027 | 0.517319 | 0.239156 |
| 1746 | Tunisia | 2014 | 4.763595 | 9.259631 | 0.680261 | 65.820000 | 0.588934 | -0.231928 | 0.783134 | 0.502728 | 0.320770 |
| 1747 | Tunisia | 2015 | 5.131612 | 9.261008 | 0.609470 | 66.000000 | 0.711373 | -0.226031 | 0.814825 | 0.572956 | 0.319542 |
| 1748 | Tunisia | 2016 | 4.521453 | 9.261508 | 0.701822 | 66.300003 | 0.614438 | -0.164950 | 0.810746 | 0.612341 | 0.378108 |
| 1749 | Tunisia | 2017 | 4.124343 | 9.269105 | 0.717382 | 66.599998 | 0.477957 | -0.218600 | 0.868827 | 0.420962 | 0.377197 |
| 1750 | Tunisia | 2018 | 4.741132 | 9.283942 | 0.732954 | 66.900002 | 0.649680 | -0.191059 | 0.840117 | 0.591727 | 0.365014 |
| 1751 | Tunisia | 2019 | 4.315480 | 9.283180 | 0.609589 | 67.199997 | 0.659332 | -0.208865 | 0.888905 | 0.538935 | 0.433413 |
| 1752 | Tunisia | 2020 | 4.730811 | 9.230624 | 0.719013 | 67.500000 | 0.667758 | -0.201814 | 0.877354 | 0.584634 | 0.438774 |
| 1753 | Turkey | 2005 | 4.718734 | 9.809252 | 0.819936 | 62.599998 | 0.623115 | NaN | 0.876999 | 0.556581 | NaN |
| 1754 | Turkey | 2007 | 5.623472 | 9.902598 | 0.792273 | 63.320000 | 0.459312 | -0.178247 | 0.799733 | 0.650955 | 0.395127 |
| 1755 | Turkey | 2008 | 5.118232 | 9.899062 | 0.644874 | 63.680000 | 0.415498 | -0.188817 | 0.785391 | 0.614249 | 0.345338 |
| 1756 | Turkey | 2009 | 5.212842 | 9.838136 | 0.754646 | 64.040001 | 0.455817 | -0.227120 | 0.852887 | 0.598295 | 0.316302 |
| 1757 | Turkey | 2010 | 5.490347 | 9.905599 | 0.794905 | 64.400002 | 0.514920 | -0.187196 | 0.810896 | 0.651793 | 0.327066 |
| 1758 | Turkey | 2011 | 5.271944 | 9.995656 | 0.691902 | 64.639999 | 0.445607 | -0.241874 | 0.648596 | 0.621293 | 0.379784 |
| 1759 | Turkey | 2012 | 5.309076 | 10.026114 | 0.739281 | 64.879997 | 0.470903 | -0.215605 | 0.701850 | 0.644781 | 0.334833 |
| 1760 | Turkey | 2013 | 4.888177 | 10.090672 | 0.795451 | 65.120003 | 0.540723 | -0.229339 | 0.698065 | 0.634615 | 0.391874 |
| 1761 | Turkey | 2014 | 5.579794 | 10.124029 | 0.863288 | 65.360001 | 0.649196 | -0.023702 | 0.764014 | 0.483359 | 0.377325 |
| 1762 | Turkey | 2015 | 5.514465 | 10.166448 | 0.851225 | 65.599998 | 0.653197 | -0.016286 | 0.806076 | 0.460246 | 0.382291 |
| 1763 | Turkey | 2016 | 5.326222 | 10.181467 | 0.879995 | 66.000000 | 0.644147 | -0.065029 | 0.763707 | 0.465151 | 0.389963 |
| 1764 | Turkey | 2017 | 5.607262 | 10.237606 | 0.876468 | 66.400002 | 0.644434 | -0.237211 | 0.670911 | 0.449801 | 0.312846 |
| 1765 | Turkey | 2018 | 5.185689 | 10.250577 | 0.847027 | 66.800003 | 0.528629 | -0.175576 | 0.804879 | 0.434654 | 0.350773 |
| 1766 | Turkey | 2019 | 4.872074 | 10.245920 | 0.791656 | 67.199997 | 0.631084 | -0.135583 | 0.760442 | 0.422227 | 0.368089 |
| 1767 | Turkey | 2020 | 4.861554 | 10.219084 | 0.856730 | 67.599998 | 0.510386 | -0.110889 | 0.774417 | 0.384292 | 0.440387 |
| 1768 | Turkmenistan | 2009 | 6.567713 | 8.989171 | 0.923846 | 59.439999 | NaN | -0.101684 | NaN | 0.780770 | 0.151584 |
| 1769 | Turkmenistan | 2011 | 5.791755 | 9.181697 | 0.964419 | 60.040001 | NaN | 0.018397 | NaN | 0.639033 | 0.122068 |
| 1770 | Turkmenistan | 2012 | 5.463827 | 9.268988 | 0.945841 | 60.279999 | 0.785563 | -0.122812 | NaN | 0.584448 | 0.116881 |
| 1771 | Turkmenistan | 2013 | 5.391763 | 9.347593 | 0.845733 | 60.520000 | 0.704529 | -0.071448 | NaN | 0.598716 | 0.159606 |
| 1772 | Turkmenistan | 2014 | 5.787379 | 9.427173 | 0.908927 | 60.759998 | 0.804678 | 0.031971 | NaN | 0.695216 | 0.153950 |
| 1773 | Turkmenistan | 2015 | 5.791460 | 9.472206 | 0.960158 | 61.000000 | 0.701358 | 0.092775 | NaN | 0.705348 | 0.301039 |
| 1774 | Turkmenistan | 2016 | 5.887052 | 9.515066 | 0.929032 | 61.400002 | 0.748504 | 0.004624 | NaN | 0.636389 | 0.255499 |
| 1775 | Turkmenistan | 2017 | 5.229149 | 9.561351 | 0.908455 | 61.799999 | 0.720399 | 0.066041 | NaN | 0.520885 | 0.349628 |
| 1776 | Turkmenistan | 2018 | 4.620602 | 9.605440 | 0.984489 | 62.200001 | 0.857774 | 0.259659 | NaN | 0.612210 | 0.189025 |
| 1777 | Turkmenistan | 2019 | 5.474300 | 9.651184 | 0.981502 | 62.599998 | 0.891527 | 0.284881 | NaN | 0.509915 | 0.183343 |
| 1778 | Uganda | 2006 | 3.733584 | 7.369865 | 0.760256 | 46.480000 | 0.746723 | -0.041043 | 0.806589 | 0.589651 | 0.254418 |
| 1779 | Uganda | 2007 | 4.455839 | 7.419120 | 0.844879 | 47.459999 | 0.707961 | -0.000834 | 0.880529 | 0.708058 | 0.227878 |
| 1780 | Uganda | 2008 | 4.568619 | 7.471063 | 0.812828 | 48.439999 | 0.577934 | -0.054836 | 0.848459 | 0.640577 | 0.239573 |
| 1781 | Uganda | 2009 | 4.611986 | 7.505189 | 0.852087 | 49.419998 | 0.760231 | -0.037409 | 0.840423 | 0.640410 | 0.296116 |
| 1782 | Uganda | 2010 | 4.192882 | 7.528168 | 0.830155 | 50.400002 | 0.800667 | -0.014679 | 0.854992 | 0.647654 | 0.251242 |
| 1783 | Uganda | 2011 | 4.826001 | 7.586103 | 0.881751 | 51.220001 | 0.732974 | 0.031504 | 0.830124 | 0.678213 | 0.254482 |
| 1784 | Uganda | 2012 | 4.309238 | 7.591943 | 0.884722 | 52.040001 | 0.649463 | 0.081127 | 0.837546 | 0.753984 | 0.265322 |
| 1785 | Uganda | 2013 | 3.709579 | 7.594839 | 0.878275 | 52.860001 | 0.763021 | 0.052719 | 0.820481 | 0.675636 | 0.346357 |
| 1786 | Uganda | 2014 | 3.769919 | 7.611118 | 0.821206 | 53.680000 | 0.834174 | 0.009276 | 0.897995 | 0.680730 | 0.396720 |
| 1787 | Uganda | 2015 | 4.237687 | 7.626735 | 0.746633 | 54.500000 | 0.757835 | 0.135057 | 0.872740 | 0.702905 | 0.352848 |
| 1788 | Uganda | 2016 | 4.233261 | 7.636911 | 0.753540 | 54.900002 | 0.739410 | 0.131759 | 0.811070 | 0.667976 | 0.410067 |
| 1789 | Uganda | 2017 | 4.000517 | 7.637649 | 0.739956 | 55.299999 | 0.772344 | 0.059689 | 0.815770 | 0.703376 | 0.400026 |
| 1790 | Uganda | 2018 | 4.321715 | 7.660166 | 0.739841 | 55.700001 | 0.728513 | 0.078885 | 0.856106 | 0.685169 | 0.390319 |
| 1791 | Uganda | 2019 | 4.948051 | 7.687653 | 0.805487 | 56.099998 | 0.704377 | 0.138821 | 0.825613 | 0.693082 | 0.385221 |
| 1792 | Uganda | 2020 | 4.640910 | 7.684450 | 0.800461 | 56.500000 | 0.687482 | 0.147118 | 0.877587 | 0.698949 | 0.424707 |
| 1793 | Ukraine | 2006 | 4.803954 | 9.380307 | 0.852453 | 60.119999 | 0.623814 | -0.257109 | 0.929431 | 0.621520 | 0.249234 |
| 1794 | Ukraine | 2007 | 5.252182 | 9.459466 | 0.820094 | 60.639999 | 0.493922 | -0.240675 | 0.967940 | 0.636170 | 0.207652 |
| 1795 | Ukraine | 2008 | 5.172380 | 9.487659 | 0.860014 | 61.160000 | 0.486627 | -0.264713 | 0.929175 | 0.573153 | 0.185806 |
| 1796 | Ukraine | 2009 | 5.165639 | 9.332416 | 0.845293 | 61.680000 | 0.460348 | -0.241401 | 0.962244 | 0.583073 | 0.189014 |
| 1797 | Ukraine | 2010 | 5.057561 | 9.374015 | 0.883555 | 62.200001 | 0.483833 | -0.188660 | 0.953752 | 0.512683 | 0.227200 |
| 1798 | Ukraine | 2011 | 5.083133 | 9.430825 | 0.859459 | 62.500000 | 0.578669 | -0.227612 | 0.932535 | 0.590430 | 0.219648 |
| 1799 | Ukraine | 2012 | 5.030342 | 9.435678 | 0.897573 | 62.799999 | 0.563650 | -0.223113 | 0.896237 | 0.570338 | 0.192819 |
| 1800 | Ukraine | 2013 | 4.710803 | 9.437689 | 0.896510 | 63.099998 | 0.568716 | -0.216286 | 0.937324 | 0.643462 | 0.224596 |
| 1801 | Ukraine | 2014 | 4.297330 | 9.426173 | 0.876760 | 63.400002 | 0.533267 | 0.083829 | 0.926789 | 0.594337 | 0.248560 |
| 1802 | Ukraine | 2015 | 3.964543 | 9.326974 | 0.909440 | 63.700001 | 0.430592 | -0.033402 | 0.952473 | 0.574076 | 0.241076 |
| 1803 | Ukraine | 2016 | 4.028690 | 9.353109 | 0.884961 | 64.000000 | 0.502542 | 0.010513 | 0.891075 | 0.588722 | 0.219624 |
| 1804 | Ukraine | 2017 | 4.311067 | 9.381865 | 0.858325 | 64.300003 | 0.598876 | -0.002278 | 0.936764 | 0.597112 | 0.234764 |
| 1805 | Ukraine | 2018 | 4.661909 | 9.420440 | 0.900937 | 64.599998 | 0.663055 | -0.074371 | 0.942961 | 0.608771 | 0.221851 |
| 1806 | Ukraine | 2019 | 4.701762 | 9.458004 | 0.882726 | 64.900002 | 0.715312 | -0.081017 | 0.885005 | 0.634228 | 0.201132 |
| 1807 | Ukraine | 2020 | 5.269676 | 9.427874 | 0.884686 | 65.199997 | 0.784273 | 0.126344 | 0.945669 | 0.687721 | 0.284736 |
| 1808 | United Arab Emirates | 2006 | 6.734222 | 11.367043 | 0.903410 | 65.919998 | 0.897557 | -0.032504 | 0.203359 | 0.746001 | 0.275255 |
| 1809 | United Arab Emirates | 2009 | 6.866063 | 10.974636 | 0.885089 | 66.279999 | 0.848822 | 0.019040 | 0.338876 | 0.770118 | 0.287074 |
| 1810 | United Arab Emirates | 2010 | 7.097456 | 10.913667 | 0.911762 | 66.400002 | 0.877751 | 0.056747 | 0.355116 | 0.762652 | 0.233014 |
| 1811 | United Arab Emirates | 2011 | 7.118701 | 10.935309 | 0.881369 | 66.419998 | 0.889463 | 0.071289 | NaN | 0.762837 | 0.215870 |
| 1812 | United Arab Emirates | 2012 | 7.217767 | 10.957638 | 0.855877 | 66.440002 | 0.919793 | NaN | NaN | 0.767661 | 0.223985 |
| 1813 | United Arab Emirates | 2013 | 6.620951 | 11.000794 | 0.863716 | 66.459999 | 0.935979 | NaN | NaN | NaN | 0.291113 |
| 1814 | United Arab Emirates | 2014 | 6.539855 | 11.040978 | NaN | 66.480003 | NaN | NaN | NaN | NaN | NaN |
| 1815 | United Arab Emirates | 2015 | 6.568398 | 11.085503 | 0.824137 | 66.500000 | 0.915036 | 0.201111 | NaN | 0.760500 | 0.295733 |
| 1816 | United Arab Emirates | 2016 | 6.830950 | 11.105121 | 0.849380 | 66.699997 | 0.949120 | 0.131059 | NaN | 0.775128 | 0.244668 |
| 1817 | United Arab Emirates | 2017 | 7.039420 | 11.115185 | 0.835527 | 66.900002 | 0.962017 | 0.215843 | NaN | 0.795035 | 0.207598 |
| 1818 | United Arab Emirates | 2018 | 6.603744 | 11.111975 | 0.851041 | 67.099998 | 0.943664 | 0.053972 | NaN | 0.787243 | 0.302042 |
| 1819 | United Arab Emirates | 2019 | 6.710783 | 11.114224 | 0.861533 | 67.300003 | 0.911420 | 0.128725 | NaN | 0.793177 | 0.283763 |
| 1820 | United Arab Emirates | 2020 | 6.458392 | 11.052890 | 0.826756 | 67.500000 | 0.942162 | 0.060020 | NaN | 0.751660 | 0.298480 |
| 1821 | United Kingdom | 2005 | 6.983557 | 10.662885 | 0.978840 | 69.900002 | 0.922355 | NaN | 0.398457 | 0.864076 | 0.261732 |
| 1822 | United Kingdom | 2007 | 6.801931 | 10.699264 | 0.969870 | 70.459999 | 0.838332 | 0.336252 | 0.498093 | 0.782353 | 0.241052 |
| 1823 | United Kingdom | 2008 | 6.986464 | 10.688578 | 0.953839 | 70.739998 | 0.759144 | 0.331124 | 0.547769 | 0.818951 | 0.218297 |
| 1824 | United Kingdom | 2009 | 6.906547 | 10.637608 | 0.964429 | 71.019997 | 0.816229 | 0.341457 | 0.558927 | 0.846380 | 0.231029 |
| 1825 | United Kingdom | 2010 | 7.029364 | 10.649076 | 0.955068 | 71.300003 | 0.841307 | 0.403173 | 0.586813 | 0.862621 | 0.176343 |
| 1826 | United Kingdom | 2011 | 6.869249 | 10.656545 | 0.948711 | 71.379997 | 0.899774 | 0.336042 | 0.437595 | 0.844498 | 0.173908 |
| 1827 | United Kingdom | 2012 | 6.880784 | 10.664272 | 0.934575 | 71.459999 | 0.888970 | 0.371288 | 0.425170 | 0.844452 | 0.184245 |
| 1828 | United Kingdom | 2013 | 6.918055 | 10.678744 | 0.936884 | 71.540001 | 0.905278 | 0.346288 | 0.568043 | 0.775744 | 0.252096 |
| 1829 | United Kingdom | 2014 | 6.758148 | 10.697121 | 0.910247 | 71.620003 | 0.857040 | 0.354738 | 0.484118 | 0.793993 | 0.251140 |
| 1830 | United Kingdom | 2015 | 6.515445 | 10.712479 | 0.935986 | 71.699997 | 0.832926 | 0.300105 | 0.456134 | 0.797785 | 0.219262 |
| 1831 | United Kingdom | 2016 | 6.824284 | 10.723900 | 0.954068 | 71.900002 | 0.821192 | 0.250308 | 0.458313 | 0.775853 | 0.229587 |
| 1832 | United Kingdom | 2017 | 7.103273 | 10.735850 | 0.937495 | 72.099998 | 0.812733 | 0.291236 | 0.418611 | 0.758572 | 0.209572 |
| 1833 | United Kingdom | 2018 | 7.233445 | 10.743109 | 0.928484 | 72.300003 | 0.837508 | 0.226284 | 0.404276 | 0.783172 | 0.228276 |
| 1834 | United Kingdom | 2019 | 7.157151 | 10.751485 | 0.942681 | 72.500000 | 0.854040 | 0.270557 | 0.485092 | 0.775203 | 0.251014 |
| 1835 | United Kingdom | 2020 | 6.798177 | 10.625811 | 0.929353 | 72.699997 | 0.884624 | 0.202508 | 0.490204 | 0.758164 | 0.224655 |
| 1836 | United States | 2006 | 7.181794 | 10.923974 | 0.964572 | 68.059998 | 0.911496 | NaN | 0.600309 | 0.827417 | 0.260511 |
| 1837 | United States | 2007 | 7.512688 | 10.933051 | NaN | 68.220001 | 0.871904 | 0.197084 | 0.633035 | 0.828503 | 0.231679 |
| 1838 | United States | 2008 | 7.280386 | 10.922226 | 0.952587 | 68.379997 | 0.877956 | 0.254692 | 0.668495 | 0.871968 | 0.226823 |
| 1839 | United States | 2009 | 7.158032 | 10.887765 | 0.911794 | 68.540001 | 0.830684 | 0.200643 | 0.665394 | 0.843484 | 0.261661 |
| 1840 | United States | 2010 | 7.163616 | 10.904800 | 0.926159 | 68.699997 | 0.828044 | 0.243921 | 0.689583 | 0.860642 | 0.231053 |
| 1841 | United States | 2011 | 7.115139 | 10.912990 | 0.921705 | 68.680000 | 0.863202 | 0.160684 | 0.696926 | 0.836360 | 0.273379 |
| 1842 | United States | 2012 | 7.026227 | 10.927963 | 0.903192 | 68.660004 | 0.822662 | 0.214699 | 0.710034 | 0.833771 | 0.259644 |
| 1843 | United States | 2013 | 7.249285 | 10.939349 | 0.925397 | 68.639999 | 0.792256 | 0.273915 | 0.746894 | 0.813678 | 0.260328 |
| 1844 | United States | 2014 | 7.151114 | 10.956298 | 0.902097 | 68.620003 | 0.866077 | 0.221340 | 0.702267 | 0.834294 | 0.281265 |
| 1845 | United States | 2015 | 6.863947 | 10.977393 | 0.903571 | 68.599998 | 0.848753 | 0.219460 | 0.697543 | 0.813908 | 0.274688 |
| 1846 | United States | 2016 | 6.803600 | 10.985777 | 0.896751 | 68.500000 | 0.757893 | 0.144048 | 0.738920 | 0.805674 | 0.264204 |
| 1847 | United States | 2017 | 6.991759 | 11.001395 | 0.921003 | 68.400002 | 0.868497 | 0.197317 | 0.681191 | 0.826555 | 0.268269 |
| 1848 | United States | 2018 | 6.882685 | 11.025024 | 0.903856 | 68.300003 | 0.824607 | 0.116116 | 0.709928 | 0.815383 | 0.292226 |
| 1849 | United States | 2019 | 6.943701 | 11.043353 | 0.916691 | 68.199997 | 0.836139 | 0.144299 | 0.706716 | 0.814985 | 0.243834 |
| 1850 | United States | 2020 | 7.028088 | 11.000656 | 0.937370 | 68.099998 | 0.850447 | 0.034103 | 0.678125 | 0.787372 | 0.295499 |
| 1851 | Uruguay | 2006 | 5.785868 | 9.542817 | 0.911877 | 67.440002 | 0.806579 | -0.112544 | 0.476627 | 0.784314 | 0.306158 |
| 1852 | Uruguay | 2007 | 5.693946 | 9.604274 | 0.874577 | 67.580002 | 0.786249 | -0.165002 | 0.614029 | 0.776779 | 0.273572 |
| 1853 | Uruguay | 2008 | 5.663870 | 9.671038 | 0.879114 | 67.720001 | 0.807930 | -0.142880 | 0.596767 | 0.751168 | 0.264006 |
| 1854 | Uruguay | 2009 | 6.296223 | 9.709771 | 0.923861 | 67.860001 | 0.825049 | -0.118288 | 0.543948 | 0.793431 | 0.254544 |
| 1855 | Uruguay | 2010 | 6.062011 | 9.782048 | 0.893040 | 68.000000 | 0.832241 | -0.158050 | 0.471376 | 0.806707 | 0.231179 |
| 1856 | Uruguay | 2011 | 6.554047 | 9.829510 | 0.891282 | 68.139999 | 0.851442 | -0.080015 | 0.556286 | 0.805346 | 0.252250 |
| 1857 | Uruguay | 2012 | 6.449728 | 9.861304 | 0.864694 | 68.279999 | 0.870590 | 0.067105 | 0.615350 | 0.787868 | 0.214203 |
| 1858 | Uruguay | 2013 | 6.444465 | 9.903544 | 0.917280 | 68.419998 | 0.888278 | -0.043126 | 0.585632 | 0.826393 | 0.253229 |
| 1859 | Uruguay | 2014 | 6.561444 | 9.932180 | 0.901898 | 68.559998 | 0.904333 | -0.072777 | 0.533495 | 0.869249 | 0.251499 |
| 1860 | Uruguay | 2015 | 6.628080 | 9.932483 | 0.891493 | 68.699997 | 0.916880 | -0.032266 | 0.673476 | 0.892661 | 0.299538 |
| 1861 | Uruguay | 2016 | 6.171485 | 9.945693 | 0.900381 | 68.800003 | 0.886372 | -0.071944 | 0.676213 | 0.841549 | 0.283180 |
| 1862 | Uruguay | 2017 | 6.336010 | 9.967628 | 0.913802 | 68.900002 | 0.897852 | -0.091392 | 0.626582 | 0.835861 | 0.280323 |
| 1863 | Uruguay | 2018 | 6.371715 | 9.980024 | 0.917316 | 69.000000 | 0.876211 | -0.097156 | 0.682916 | 0.876920 | 0.274946 |
| 1864 | Uruguay | 2019 | 6.600337 | 9.978644 | 0.933471 | 69.099998 | 0.902679 | -0.095303 | 0.599400 | 0.888966 | 0.221730 |
| 1865 | Uruguay | 2020 | 6.309681 | 9.937192 | 0.921070 | 69.199997 | 0.907762 | -0.083987 | 0.491008 | 0.807351 | 0.264692 |
| 1866 | Uzbekistan | 2006 | 5.232322 | 8.192730 | 0.903067 | 61.439999 | 0.784301 | -0.115492 | 0.608808 | 0.727946 | 0.195058 |
| 1867 | Uzbekistan | 2008 | 5.311368 | 8.339396 | 0.894026 | 62.320000 | 0.831269 | -0.023097 | NaN | 0.713683 | 0.186682 |
| 1868 | Uzbekistan | 2009 | 5.260721 | 8.399955 | 0.904678 | 62.759998 | NaN | 0.013131 | 0.610258 | 0.735559 | 0.158657 |
| 1869 | Uzbekistan | 2010 | 5.095342 | 8.444950 | 0.903226 | 63.200001 | NaN | -0.030090 | 0.518720 | 0.775874 | 0.151883 |
| 1870 | Uzbekistan | 2011 | 5.738744 | 8.493077 | 0.924071 | 63.400002 | 0.934133 | 0.042083 | 0.521862 | 0.787154 | 0.122773 |
| 1871 | Uzbekistan | 2012 | 6.019332 | 8.549520 | 0.933141 | 63.599998 | 0.913550 | -0.037380 | 0.463375 | 0.785679 | 0.118177 |
| 1872 | Uzbekistan | 2013 | 5.939986 | 8.607008 | 0.962781 | 63.799999 | 0.949540 | -0.034047 | 0.433932 | 0.749193 | 0.130197 |
| 1873 | Uzbekistan | 2014 | 6.049212 | 8.659472 | 0.952406 | 64.000000 | 0.954481 | 0.061329 | 0.536461 | 0.804545 | 0.106158 |
| 1874 | Uzbekistan | 2015 | 5.972364 | 8.713864 | 0.968225 | 64.199997 | 0.979937 | 0.374668 | 0.470917 | 0.839981 | 0.103494 |
| 1875 | Uzbekistan | 2016 | 5.892539 | 8.755632 | 0.945102 | 64.500000 | 0.983803 | 0.208193 | NaN | 0.841676 | 0.146898 |
| 1876 | Uzbekistan | 2017 | 6.421448 | 8.782446 | 0.942131 | 64.800003 | 0.985178 | 0.122524 | 0.464642 | 0.838989 | 0.202737 |
| 1877 | Uzbekistan | 2018 | 6.205460 | 8.818110 | 0.920821 | 65.099998 | 0.969898 | 0.317585 | 0.520360 | 0.825422 | 0.208660 |
| 1878 | Uzbekistan | 2019 | 6.154049 | 8.853480 | 0.915276 | 65.400002 | 0.970295 | 0.304298 | 0.511197 | 0.844809 | 0.219746 |
| 1879 | Venezuela | 2005 | 7.169621 | 9.313096 | 0.955278 | 65.400002 | 0.838198 | NaN | 0.719800 | 0.819065 | 0.233014 |
| 1880 | Venezuela | 2006 | 6.525146 | 9.459522 | 0.946310 | 65.459999 | 0.798281 | -0.031057 | 0.646171 | 0.858956 | 0.178483 |
| 1881 | Venezuela | 2008 | 6.257771 | 9.700688 | 0.922434 | 65.580002 | 0.678401 | -0.225003 | 0.776103 | 0.801530 | 0.224191 |
| 1882 | Venezuela | 2009 | 7.188803 | 9.542343 | 0.944541 | 65.639999 | 0.676886 | -0.116365 | 0.827594 | 0.824885 | 0.180226 |
| 1883 | Venezuela | 2010 | 7.478455 | 9.716555 | 0.931576 | 65.699997 | 0.768257 | -0.154883 | 0.754269 | 0.861522 | 0.129686 |
| 1884 | Venezuela | 2011 | 6.579789 | 9.822392 | 0.930620 | 65.739998 | 0.766335 | -0.226387 | 0.771539 | 0.827956 | 0.198666 |
| 1885 | Venezuela | 2012 | 7.066577 | 9.826082 | 0.931630 | 65.779999 | 0.804109 | -0.192730 | 0.743374 | 0.857873 | 0.176308 |
| 1886 | Venezuela | 2013 | 6.552796 | 9.738845 | 0.896301 | 65.820000 | 0.641965 | -0.219742 | 0.837300 | 0.839730 | 0.237609 |
| 1887 | Venezuela | 2014 | 6.136096 | 9.557058 | 0.903956 | 65.860001 | 0.569962 | -0.198841 | 0.826535 | 0.810578 | 0.243604 |
| 1888 | Venezuela | 2015 | 5.568800 | 9.001046 | 0.911087 | 65.900002 | 0.512159 | -0.116937 | 0.813097 | 0.867409 | 0.222635 |
| 1889 | Venezuela | 2016 | 4.041115 | 9.010295 | 0.901949 | 66.099998 | 0.457602 | -0.154931 | 0.890125 | 0.688201 | 0.391754 |
| 1890 | Venezuela | 2017 | 5.070751 | 9.073104 | 0.895879 | 66.300003 | 0.635505 | -0.168757 | 0.843969 | 0.725643 | 0.362985 |
| 1891 | Venezuela | 2018 | 5.005663 | NaN | 0.886882 | 66.500000 | 0.610855 | NaN | 0.827560 | 0.759221 | 0.373658 |
| 1892 | Venezuela | 2019 | 5.080803 | NaN | 0.887672 | 66.699997 | 0.625526 | NaN | 0.839340 | 0.761240 | 0.350950 |
| 1893 | Venezuela | 2020 | 4.573830 | NaN | 0.805224 | 66.900002 | 0.611815 | NaN | 0.811319 | 0.722391 | 0.396250 |
| 1894 | Vietnam | 2006 | 5.293660 | 8.334977 | 0.887664 | 65.860001 | 0.885792 | 0.014574 | NaN | 0.682261 | 0.203979 |
| 1895 | Vietnam | 2007 | 5.421688 | 8.394412 | 0.856023 | 66.019997 | 0.917836 | 0.089205 | 0.753934 | 0.587590 | 0.205932 |
| 1896 | Vietnam | 2008 | 5.480425 | 8.439887 | 0.804560 | 66.180000 | 0.888625 | 0.200575 | 0.789238 | 0.665097 | 0.217538 |
| 1897 | Vietnam | 2009 | 5.304265 | 8.482665 | 0.815026 | 66.339996 | 0.834134 | -0.061870 | 0.837870 | 0.582757 | 0.189930 |
| 1898 | Vietnam | 2010 | 5.295781 | 8.534918 | 0.786611 | 66.500000 | 0.831494 | -0.005769 | 0.742637 | 0.685243 | 0.215798 |
| 1899 | Vietnam | 2011 | 5.767344 | 8.585228 | 0.897655 | 66.660004 | 0.818404 | 0.104993 | 0.742162 | 0.531590 | 0.192669 |
| 1900 | Vietnam | 2012 | 5.534570 | 8.625951 | 0.775009 | 66.820000 | 0.856053 | -0.110290 | 0.814885 | 0.615128 | 0.221356 |
| 1901 | Vietnam | 2013 | 5.022699 | 8.668217 | 0.759477 | 66.980003 | 0.919607 | -0.027052 | 0.771246 | 0.718431 | 0.165225 |
| 1902 | Vietnam | 2014 | 5.084923 | 8.715796 | 0.792168 | 67.139999 | NaN | 0.000040 | NaN | 0.701386 | 0.240607 |
| 1903 | Vietnam | 2015 | 5.076315 | 8.770014 | 0.848677 | 67.300003 | NaN | 0.085506 | NaN | 0.642237 | 0.232416 |
| 1904 | Vietnam | 2016 | 5.062267 | 8.819946 | 0.876324 | 67.500000 | 0.894351 | -0.089814 | 0.799240 | 0.536226 | 0.222550 |
| 1905 | Vietnam | 2017 | 5.175279 | 8.875670 | NaN | 67.699997 | NaN | NaN | NaN | NaN | NaN |
| 1906 | Vietnam | 2018 | 5.295547 | 8.934111 | 0.831945 | 67.900002 | 0.909260 | -0.040764 | 0.808423 | 0.692222 | 0.191061 |
| 1907 | Vietnam | 2019 | 5.467451 | 8.992331 | 0.847592 | 68.099998 | 0.952469 | -0.125531 | 0.787889 | 0.751160 | 0.185610 |
| 1908 | Yemen | 2007 | 4.477133 | 8.214067 | 0.824969 | 53.400002 | 0.672685 | 0.011009 | NaN | 0.591898 | 0.378784 |
| 1909 | Yemen | 2009 | 4.809259 | 8.277721 | 0.756430 | 54.000000 | 0.644229 | -0.052247 | 0.832427 | 0.583224 | 0.374160 |
| 1910 | Yemen | 2010 | 4.350313 | 8.453350 | 0.726612 | 54.299999 | 0.659284 | -0.104334 | 0.853403 | 0.582427 | 0.308333 |
| 1911 | Yemen | 2011 | 3.746256 | 8.336312 | 0.662680 | 54.299999 | 0.638211 | -0.173486 | 0.753882 | 0.502691 | 0.284863 |
| 1912 | Yemen | 2012 | 4.060601 | 8.236007 | 0.681678 | 54.299999 | 0.705815 | -0.170729 | 0.793233 | 0.501776 | 0.262817 |
| 1913 | Yemen | 2013 | 4.217679 | 8.241937 | 0.693905 | 54.299999 | 0.542547 | -0.179008 | 0.885197 | 0.558500 | 0.265685 |
| 1914 | Yemen | 2014 | 3.967958 | 8.116539 | 0.638252 | 54.299999 | 0.663909 | -0.157303 | 0.885429 | 0.610585 | 0.275674 |
| 1915 | Yemen | 2015 | 2.982674 | 7.857512 | 0.668683 | 54.299999 | 0.609981 | -0.139383 | 0.829098 | 0.507435 | 0.321357 |
| 1916 | Yemen | 2016 | 3.825631 | 7.715108 | 0.775407 | 55.099998 | 0.532964 | -0.150821 | NaN | 0.469345 | 0.227925 |
| 1917 | Yemen | 2017 | 3.253560 | 7.578437 | 0.789555 | 55.900002 | 0.595191 | -0.146712 | NaN | 0.455182 | 0.295064 |
| 1918 | Yemen | 2018 | 3.057514 | NaN | 0.789422 | 56.700001 | 0.552726 | NaN | 0.792587 | 0.461114 | 0.314870 |
| 1919 | Yemen | 2019 | 4.196913 | NaN | 0.870043 | 57.500000 | 0.651308 | NaN | 0.798228 | 0.542806 | 0.213043 |
| 1920 | Zambia | 2006 | 4.824455 | 7.817309 | 0.797665 | 44.259998 | 0.720972 | -0.005999 | 0.785281 | 0.700788 | 0.226278 |
| 1921 | Zambia | 2007 | 3.998293 | 7.870825 | 0.687989 | 45.720001 | 0.682005 | -0.066975 | 0.947914 | 0.686748 | 0.245637 |
| 1922 | Zambia | 2008 | 4.730263 | 7.918427 | 0.624418 | 47.180000 | 0.716994 | 0.055702 | 0.890299 | 0.744144 | 0.205723 |
| 1923 | Zambia | 2009 | 5.260361 | 7.978490 | 0.781926 | 48.639999 | 0.696183 | -0.095979 | 0.916553 | 0.727505 | 0.122659 |
| 1924 | Zambia | 2011 | 4.999114 | 8.071311 | 0.864023 | 50.840000 | 0.662850 | 0.002801 | 0.882150 | 0.833214 | 0.204070 |
| 1925 | Zambia | 2012 | 5.013375 | 8.113511 | 0.780023 | 51.580002 | 0.787760 | 0.007661 | 0.806394 | 0.725965 | 0.250368 |
| 1926 | Zambia | 2013 | 5.243996 | 8.131451 | 0.761312 | 52.320000 | 0.769912 | -0.104419 | 0.732268 | 0.734979 | 0.307960 |
| 1927 | Zambia | 2014 | 4.345837 | 8.146145 | 0.706223 | 53.060001 | 0.811825 | -0.010734 | 0.808841 | 0.692035 | 0.327384 |
| 1928 | Zambia | 2015 | 4.843164 | 8.144258 | 0.691483 | 53.799999 | 0.758654 | -0.038819 | 0.871020 | 0.690034 | 0.381731 |
| 1929 | Zambia | 2016 | 4.347544 | 8.151297 | 0.767047 | 54.299999 | 0.811575 | 0.122350 | 0.770644 | 0.730680 | 0.372241 |
| 1930 | Zambia | 2017 | 3.932777 | 8.156224 | 0.743754 | 54.799999 | 0.823169 | 0.140323 | 0.739541 | 0.684623 | 0.387189 |
| 1931 | Zambia | 2018 | 4.041488 | 8.166652 | 0.717720 | 55.299999 | 0.790626 | 0.048121 | 0.810731 | 0.702698 | 0.350963 |
| 1932 | Zambia | 2019 | 3.306797 | 8.154642 | 0.637894 | 55.799999 | 0.811040 | 0.077462 | 0.831956 | 0.743407 | 0.394385 |
| 1933 | Zambia | 2020 | 4.837992 | 8.116580 | 0.766872 | 56.299999 | 0.750422 | 0.056029 | 0.809750 | 0.691082 | 0.344526 |
| 1934 | Zimbabwe | 2006 | 3.826268 | 7.711109 | 0.821656 | 41.580002 | 0.431110 | -0.076397 | 0.904757 | 0.715229 | 0.297147 |
| 1935 | Zimbabwe | 2007 | 3.280247 | 7.665664 | 0.828113 | 42.860001 | 0.455957 | -0.082092 | 0.946287 | 0.660861 | 0.264989 |
| 1936 | Zimbabwe | 2008 | 3.174264 | 7.461205 | 0.843475 | 44.139999 | 0.343556 | -0.089681 | 0.963846 | 0.630983 | 0.250060 |
| 1937 | Zimbabwe | 2009 | 4.055914 | 7.562871 | 0.805781 | 45.419998 | 0.411089 | -0.077691 | 0.930818 | 0.735503 | 0.218419 |
| 1938 | Zimbabwe | 2010 | 4.681570 | 7.728944 | 0.856638 | 46.700001 | 0.664718 | -0.092813 | 0.828361 | 0.747702 | 0.122150 |
| 1939 | Zimbabwe | 2011 | 4.845642 | 7.846308 | 0.864694 | 48.119999 | 0.632978 | -0.087876 | 0.829800 | 0.781189 | 0.210544 |
| 1940 | Zimbabwe | 2012 | 4.955101 | 7.983468 | 0.896476 | 49.540001 | 0.469531 | -0.102505 | 0.858691 | 0.669279 | 0.177311 |
| 1941 | Zimbabwe | 2013 | 4.690188 | 7.985391 | 0.799274 | 50.959999 | 0.575884 | -0.104101 | 0.830937 | 0.711885 | 0.182288 |
| 1942 | Zimbabwe | 2014 | 4.184451 | 7.991335 | 0.765839 | 52.380001 | 0.642034 | -0.073880 | 0.820217 | 0.725214 | 0.239111 |
| 1943 | Zimbabwe | 2015 | 3.703191 | 7.992339 | 0.735800 | 53.799999 | 0.667193 | -0.123171 | 0.810457 | 0.715079 | 0.178861 |
| 1944 | Zimbabwe | 2016 | 3.735400 | 7.984372 | 0.768425 | 54.400002 | 0.732971 | -0.094634 | 0.723612 | 0.737636 | 0.208555 |
| 1945 | Zimbabwe | 2017 | 3.638300 | 8.015738 | 0.754147 | 55.000000 | 0.752826 | -0.097645 | 0.751208 | 0.806428 | 0.224051 |
| 1946 | Zimbabwe | 2018 | 3.616480 | 8.048798 | 0.775388 | 55.599998 | 0.762675 | -0.068427 | 0.844209 | 0.710119 | 0.211726 |
| 1947 | Zimbabwe | 2019 | 2.693523 | 7.950132 | 0.759162 | 56.200001 | 0.631908 | -0.063791 | 0.830652 | 0.716004 | 0.235354 |
| 1948 | Zimbabwe | 2020 | 3.159802 | 7.828757 | 0.717243 | 56.799999 | 0.643303 | -0.008696 | 0.788523 | 0.702573 | 0.345736 |
happiness = pd.DataFrame(happiness)
excel_happiness = "happiness.xlsx"
happiness.to_excel(excel_happiness, index=False)
energy2010to2020['year'] = energy2010to2020['year'].astype(int)
countries_to_plot = ["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"]
plt.figure(figsize=(14, 8))
for country in countries_to_plot:
country_data = energy2010to2020[(energy2010to2020['Country_name'] == country) &
(energy2010to2020['year'].between(2010, 2020))]
plt.plot(country_data['year'], country_data['Energy_consumption_per_capita'], label=country)
plt.xlabel('Year')
plt.ylabel('Energy Consumption per Capita')
plt.title('Energy Consumption per Capita (2010-2020)',fontsize=20)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
sns.despine()
plt.tight_layout()
plt.show()
countries_to_plot = ["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"]
worldbank_gdp['year'] = worldbank_gdp['year'].astype(int)
plt.figure(figsize=(14, 8))
for country in countries_to_plot:
country_data = worldbank_gdp[(worldbank_gdp['Country_name'] == country) &
(worldbank_gdp['year'].between(2010, 2020))]
country_data = country_data.sort_values(by='year')
plt.plot(country_data['year'], country_data['GDP_per_capita'], label=country)
plt.xlabel('Year')
plt.ylabel('GDP per Capita')
plt.title('GDP per Capita (2010-2020)',fontsize=20)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
sns.despine()
plt.tight_layout()
plt.show()
countries_to_plot = ["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"]
worldbank_CO2['year'] = worldbank_CO2['year'].astype(int)
plt.figure(figsize=(14, 8))
for country in countries_to_plot:
country_data = worldbank_CO2[(worldbank_CO2['Country_name'] == country) &
(worldbank_CO2['year'].between(2010, 2020))]
country_data = country_data.sort_values(by='year')
plt.plot(country_data['year'], country_data['CO2_per_capita'], label=country)
plt.xlabel('Year')
plt.ylabel('CO2 Emission per Capita')
plt.title('CO2 Emission per Capita (2010-2020)',fontsize=20)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
sns.despine()
plt.tight_layout()
plt.show()
countries_to_plot = ["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"]
worldbank_forest['year'] = worldbank_forest['year'].astype(int)
plt.figure(figsize=(14, 8))
for country in countries_to_plot:
# Filter and sort the data by year
country_data = worldbank_forest[(worldbank_forest['Country_name'] == country) &
(worldbank_forest['year'].between(2010, 2020))]
country_data = country_data.sort_values(by='year')
plt.plot(country_data['year'], country_data['ForestArea'], label=country)
plt.xlabel('Year')
plt.ylabel('Forest Area')
plt.title('Forest Area (2010-2020)',fontsize=20)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
sns.despine()
plt.tight_layout()
plt.show()
worldbank_forest['year'] =worldbank_forest['year'].astype(int)
filtered_worldbank_forest = worldbank_forest[(worldbank_forest['Country_name'].isin(["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"])) &
(worldbank_forest['year'].between(2010, 2020))]
filtered_worldbank_forest = filtered_worldbank_forest[['Country_name', 'year', 'ForestArea']]
filtered_worldbank_forest
worldbank_population['year'] = worldbank_population['year'].astype(int)
filtered_worldbank_population = worldbank_population[(worldbank_population['Country_name'].isin(["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"])) &
(worldbank_population['year'].between(2010, 2020))]
filtered_worldbank_population = filtered_worldbank_population[['Country_name', 'year', 'Population']]
filtered_worldbank_population
merged_data = pd.merge(filtered_worldbank_forest, filtered_worldbank_population,on=['Country_name', 'year'])
merged_data['Forest_Area_per_capita'] = merged_data['ForestArea'] * 1000 / merged_data['Population']
merged_data
| Country_name | year | ForestArea | Population | Forest_Area_per_capita | |
|---|---|---|---|---|---|
| 0 | Australia | 2020 | 1340051.00 | 2.564925e+07 | 52.245235 |
| 1 | Australia | 2019 | 1340051.00 | 2.533483e+07 | 52.893633 |
| 2 | Australia | 2018 | 1340051.00 | 2.496326e+07 | 53.680934 |
| 3 | Australia | 2017 | 1340174.00 | 2.459259e+07 | 54.495037 |
| 4 | Australia | 2016 | 1340372.00 | 2.419091e+07 | 55.408092 |
| 5 | Australia | 2015 | 1330945.00 | 2.381600e+07 | 55.884501 |
| 6 | Australia | 2014 | 1323848.20 | 2.347569e+07 | 56.392312 |
| 7 | Australia | 2013 | 1316751.40 | 2.312813e+07 | 56.932898 |
| 8 | Australia | 2012 | 1309654.60 | 2.273346e+07 | 57.609106 |
| 9 | Australia | 2011 | 1302557.80 | 2.234002e+07 | 58.306016 |
| 10 | Australia | 2010 | 1295461.00 | 2.203175e+07 | 58.799732 |
| 11 | Brazil | 2020 | 4966196.00 | 2.131963e+08 | 23.294006 |
| 12 | Brazil | 2019 | 4977985.00 | 2.117829e+08 | 23.505134 |
| 13 | Brazil | 2018 | 4990514.00 | 2.101666e+08 | 23.745515 |
| 14 | Brazil | 2017 | 5000916.00 | 2.085050e+08 | 23.984638 |
| 15 | Brazil | 2016 | 5020821.00 | 2.068596e+08 | 24.271639 |
| 16 | Brazil | 2015 | 5038848.00 | 2.051882e+08 | 24.557201 |
| 17 | Brazil | 2014 | 5054239.80 | 2.034596e+08 | 24.841485 |
| 18 | Brazil | 2013 | 5069631.60 | 2.017218e+08 | 25.131802 |
| 19 | Brazil | 2012 | 5085023.40 | 1.999777e+08 | 25.427951 |
| 20 | Brazil | 2011 | 5100415.20 | 1.981853e+08 | 25.735588 |
| 21 | Brazil | 2010 | 5115807.00 | 1.963535e+08 | 26.054067 |
| 22 | China | 2020 | 2199781.80 | 1.411100e+09 | 1.558913 |
| 23 | China | 2019 | 2180986.10 | 1.407745e+09 | 1.549276 |
| 24 | China | 2018 | 2162190.40 | 1.402760e+09 | 1.541383 |
| 25 | China | 2017 | 2143394.70 | 1.396215e+09 | 1.535147 |
| 26 | China | 2016 | 2124598.67 | 1.387790e+09 | 1.530922 |
| 27 | China | 2015 | 2102942.50 | 1.379860e+09 | 1.524026 |
| 28 | China | 2014 | 2083574.76 | 1.371860e+09 | 1.518795 |
| 29 | China | 2013 | 2064207.02 | 1.363240e+09 | 1.514192 |
| 30 | China | 2012 | 2044839.28 | 1.354190e+09 | 1.510009 |
| 31 | China | 2011 | 2025471.54 | 1.345035e+09 | 1.505888 |
| 32 | China | 2010 | 2006103.80 | 1.337705e+09 | 1.499661 |
| 33 | Finland | 2020 | 224090.00 | 5.529543e+06 | 40.525953 |
| 34 | Finland | 2019 | 224090.00 | 5.521606e+06 | 40.584207 |
| 35 | Finland | 2018 | 224090.00 | 5.515525e+06 | 40.628952 |
| 36 | Finland | 2017 | 224090.00 | 5.508214e+06 | 40.682878 |
| 37 | Finland | 2016 | 224090.00 | 5.495303e+06 | 40.778461 |
| 38 | Finland | 2015 | 224090.00 | 5.479531e+06 | 40.895836 |
| 39 | Finland | 2014 | 223756.00 | 5.461512e+06 | 40.969607 |
| 40 | Finland | 2013 | 223422.00 | 5.438972e+06 | 41.077983 |
| 41 | Finland | 2012 | 223088.00 | 5.413971e+06 | 41.205984 |
| 42 | Finland | 2011 | 222754.00 | 5.388272e+06 | 41.340526 |
| 43 | Finland | 2010 | 222420.00 | 5.363352e+06 | 41.470334 |
| 44 | Germany | 2020 | 114190.00 | 8.316087e+07 | 1.373122 |
| 45 | Germany | 2019 | 114190.00 | 8.309296e+07 | 1.374244 |
| 46 | Germany | 2018 | 114190.00 | 8.290578e+07 | 1.377347 |
| 47 | Germany | 2017 | 114190.00 | 8.265700e+07 | 1.381492 |
| 48 | Germany | 2016 | 114190.00 | 8.234867e+07 | 1.386665 |
| 49 | Germany | 2015 | 114190.00 | 8.168661e+07 | 1.397904 |
| 50 | Germany | 2014 | 114170.00 | 8.098250e+07 | 1.409811 |
| 51 | Germany | 2013 | 114150.00 | 8.064560e+07 | 1.415452 |
| 52 | Germany | 2012 | 114130.00 | 8.042582e+07 | 1.419072 |
| 53 | Germany | 2011 | 114110.00 | 8.027498e+07 | 1.421489 |
| 54 | Germany | 2010 | 114090.00 | 8.177693e+07 | 1.395137 |
| 55 | India | 2020 | 721600.00 | 1.396387e+09 | 0.516762 |
| 56 | India | 2019 | 718936.00 | 1.383112e+09 | 0.519796 |
| 57 | India | 2018 | 716272.00 | 1.369003e+09 | 0.523207 |
| 58 | India | 2017 | 713608.00 | 1.354196e+09 | 0.526961 |
| 59 | India | 2016 | 710944.00 | 1.338636e+09 | 0.531096 |
| 60 | India | 2015 | 708280.00 | 1.322867e+09 | 0.535413 |
| 61 | India | 2014 | 705616.00 | 1.307247e+09 | 0.539773 |
| 62 | India | 2013 | 702952.00 | 1.291132e+09 | 0.544446 |
| 63 | India | 2012 | 700288.00 | 1.274487e+09 | 0.549466 |
| 64 | India | 2011 | 697624.00 | 1.257621e+09 | 0.554717 |
| 65 | India | 2010 | 694960.00 | 1.240614e+09 | 0.560174 |
| 66 | Israel | 2020 | 1400.00 | 9.215100e+06 | 0.151925 |
| 67 | Israel | 2019 | 1400.00 | 9.054000e+06 | 0.154628 |
| 68 | Israel | 2018 | 1400.00 | 8.882800e+06 | 0.157608 |
| 69 | Israel | 2017 | 1400.00 | 8.713300e+06 | 0.160674 |
| 70 | Israel | 2016 | 1400.00 | 8.546000e+06 | 0.163819 |
| 71 | Israel | 2015 | 1650.00 | 8.380100e+06 | 0.196895 |
| 72 | Israel | 2014 | 1628.00 | 8.215700e+06 | 0.198157 |
| 73 | Israel | 2013 | 1606.00 | 8.059500e+06 | 0.199268 |
| 74 | Israel | 2012 | 1584.00 | 7.910500e+06 | 0.200240 |
| 75 | Israel | 2011 | 1562.00 | 7.765800e+06 | 0.201138 |
| 76 | Israel | 2010 | 1540.00 | 7.623600e+06 | 0.202004 |
| 77 | New Zealand | 2020 | 98925.90 | 5.090200e+06 | 19.434580 |
| 78 | New Zealand | 2019 | 98655.20 | 4.979200e+06 | 19.813464 |
| 79 | New Zealand | 2018 | 98551.50 | 4.900600e+06 | 20.110089 |
| 80 | New Zealand | 2017 | 98508.50 | 4.813600e+06 | 20.464621 |
| 81 | New Zealand | 2016 | 98467.50 | 4.714100e+06 | 20.887868 |
| 82 | New Zealand | 2015 | 98466.10 | 4.609400e+06 | 21.362021 |
| 83 | New Zealand | 2014 | 98469.12 | 4.516500e+06 | 21.802086 |
| 84 | New Zealand | 2013 | 98472.14 | 4.442100e+06 | 22.167925 |
| 85 | New Zealand | 2012 | 98475.16 | 4.408100e+06 | 22.339593 |
| 86 | New Zealand | 2011 | 98478.18 | 4.384000e+06 | 22.463089 |
| 87 | New Zealand | 2010 | 98481.20 | 4.350700e+06 | 22.635714 |
| 88 | South Africa | 2020 | 170500.90 | 5.880193e+07 | 2.899580 |
| 89 | South Africa | 2019 | 170864.90 | 5.808706e+07 | 2.941531 |
| 90 | South Africa | 2018 | 171228.90 | 5.733964e+07 | 2.986222 |
| 91 | South Africa | 2017 | 171592.90 | 5.664121e+07 | 3.029471 |
| 92 | South Africa | 2016 | 171956.90 | 5.642227e+07 | 3.047678 |
| 93 | South Africa | 2015 | 172320.90 | 5.587650e+07 | 3.083960 |
| 94 | South Africa | 2014 | 172684.90 | 5.472955e+07 | 3.155241 |
| 95 | South Africa | 2013 | 173048.90 | 5.387362e+07 | 3.212127 |
| 96 | South Africa | 2012 | 173412.90 | 5.314503e+07 | 3.263012 |
| 97 | South Africa | 2011 | 173776.90 | 5.244332e+07 | 3.313613 |
| 98 | South Africa | 2010 | 174140.90 | 5.178492e+07 | 3.362772 |
| 99 | United States | 2020 | 3097950.00 | 3.315115e+08 | 9.344924 |
| 100 | United States | 2019 | 3097950.00 | 3.283300e+08 | 9.435478 |
| 101 | United States | 2018 | 3097950.00 | 3.268382e+08 | 9.478543 |
| 102 | United States | 2017 | 3097950.00 | 3.251221e+08 | 9.528573 |
| 103 | United States | 2016 | 3100950.00 | 3.230718e+08 | 9.598332 |
| 104 | United States | 2015 | 3100950.00 | 3.207390e+08 | 9.668142 |
| 105 | United States | 2014 | 3098200.00 | 3.183863e+08 | 9.730945 |
| 106 | United States | 2013 | 3095450.00 | 3.160599e+08 | 9.793870 |
| 107 | United States | 2012 | 3092700.00 | 3.138777e+08 | 9.853202 |
| 108 | United States | 2011 | 3089950.00 | 3.115835e+08 | 9.916925 |
| 109 | United States | 2010 | 3087200.00 | 3.093271e+08 | 9.980372 |
merged_data['year'] = merged_data['year'].astype(int)
sns.set(style="ticks")
plt.figure(figsize=(14, 8))
sns.lineplot(data=merged_data, x='year', y='Forest_Area_per_capita', hue='Country_name', marker=None)
plt.title('Forest Area per Capita (2010-2020)',fontsize=20)
plt.xlabel('Year')
plt.ylabel('Forest Area per Capita')
plt.legend(title='Country', loc='center right', bbox_to_anchor=(1.25, 0.5), frameon=False)
plt.tick_params(top=False, right=False)
sns.despine()
plt.show()
countries_to_plot = ["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"]
plt.figure(figsize=(14, 8))
for country in countries_to_plot:
country_data = happiness[(happiness['Country_name'] == country) &
(happiness['year'].between(2010, 2020))]
plt.plot(country_data['year'], country_data['Life_ladder'], label=country)
plt.xlabel('Year')
plt.ylabel('Life Ladder')
plt.title('Life Ladder Scores (2010-2020)',fontsize=20)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
sns.despine()
plt.tight_layout()
plt.show()
worldbank_population['year'] = worldbank_population['year'].astype(int)
countries_to_plot = ["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"]
plt.figure(figsize=(14, 8))
for country in countries_to_plot:
country_data = worldbank_population[(worldbank_population['Country_name'] == country) &
(worldbank_population['year'].between(2010, 2020))]
plt.plot(country_data['year'], country_data['Population'], label=country)
plt.xlabel('Year')
plt.ylabel('Population')
plt.title('Population (2010-2020)',fontsize=20)
plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
sns.despine()
plt.tight_layout()
plt.show()
filtered_energy2010to2020 = energy2010to2020[(energy2010to2020['Country_name'].isin(["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"])) &
(energy2010to2020['year'].between(2010, 2020))]
filtered_energy2010to2020
| Country_name | year | Energy_consumption_per_capita | |
|---|---|---|---|
| 2 | United States | 2010 | 300.7 |
| 4 | Brazil | 2010 | 56.0 |
| 14 | Finland | 2010 | 242.8 |
| 16 | Germany | 2010 | 169.6 |
| 39 | Israel | 2010 | 135.0 |
| 48 | Australia | 2010 | 240.5 |
| 50 | China | 2010 | 76.2 |
| 51 | India | 2010 | 18.2 |
| 55 | New Zealand | 2010 | 188.9 |
| 63 | South Africa | 2010 | 102.7 |
| 66 | United States | 2011 | 295.4 |
| 68 | Brazil | 2011 | 58.0 |
| 78 | Finland | 2011 | 225.8 |
| 80 | Germany | 2011 | 163.3 |
| 103 | Israel | 2011 | 135.6 |
| 112 | Australia | 2011 | 243.3 |
| 114 | China | 2011 | 81.8 |
| 115 | India | 2011 | 19.0 |
| 119 | New Zealand | 2011 | 187.9 |
| 127 | South Africa | 2011 | 99.9 |
| 130 | United States | 2012 | 285.4 |
| 132 | Brazil | 2012 | 58.5 |
| 142 | Finland | 2012 | 218.5 |
| 144 | Germany | 2012 | 165.1 |
| 167 | Israel | 2012 | 139.3 |
| 176 | Australia | 2012 | 236.5 |
| 178 | China | 2012 | 84.6 |
| 179 | India | 2012 | 19.8 |
| 183 | New Zealand | 2012 | 187.1 |
| 191 | South Africa | 2012 | 96.9 |
| 194 | United States | 2013 | 290.9 |
| 196 | Brazil | 2013 | 60.2 |
| 206 | Finland | 2013 | 218.8 |
| 208 | Germany | 2013 | 169.3 |
| 231 | Israel | 2013 | 127.3 |
| 240 | Australia | 2013 | 235.9 |
| 242 | China | 2013 | 87.2 |
| 243 | India | 2013 | 20.3 |
| 247 | New Zealand | 2013 | 186.2 |
| 255 | South Africa | 2013 | 95.7 |
| 258 | United States | 2014 | 291.8 |
| 260 | Brazil | 2014 | 61.1 |
| 270 | Finland | 2014 | 210.1 |
| 272 | Germany | 2014 | 161.6 |
| 295 | Israel | 2014 | 123.2 |
| 304 | Australia | 2014 | 234.8 |
| 306 | China | 2014 | 89.2 |
| 307 | India | 2014 | 21.4 |
| 311 | New Zealand | 2014 | 192.6 |
| 319 | South Africa | 2014 | 95.3 |
| 322 | United States | 2015 | 287.0 |
| 324 | Brazil | 2015 | 59.7 |
| 334 | Finland | 2015 | 207.9 |
| 336 | Germany | 2015 | 163.8 |
| 359 | Israel | 2015 | 128.0 |
| 368 | Australia | 2015 | 237.0 |
| 370 | China | 2015 | 89.9 |
| 371 | India | 2015 | 21.9 |
| 375 | New Zealand | 2015 | 192.3 |
| 383 | South Africa | 2015 | 91.9 |
| 386 | United States | 2016 | 284.7 |
| 388 | Brazil | 2016 | 57.7 |
| 398 | Finland | 2016 | 210.9 |
| 400 | Germany | 2016 | 165.7 |
| 423 | Israel | 2016 | 128.1 |
| 432 | Australia | 2016 | 234.8 |
| 434 | China | 2016 | 91.0 |
| 435 | India | 2016 | 22.6 |
| 439 | New Zealand | 2016 | 191.7 |
| 447 | South Africa | 2016 | 94.8 |
| 450 | United States | 2017 | 283.8 |
| 452 | Brazil | 2017 | 57.9 |
| 462 | Finland | 2017 | 205.7 |
| 464 | Germany | 2017 | 166.7 |
| 487 | Israel | 2017 | 131.7 |
| 496 | Australia | 2017 | 230.5 |
| 498 | China | 2017 | 93.5 |
| 499 | India | 2017 | 23.3 |
| 503 | New Zealand | 2017 | 193.2 |
| 511 | South Africa | 2017 | 92.9 |
| 514 | United States | 2018 | 292.4 |
| 516 | Brazil | 2018 | 57.8 |
| 526 | Finland | 2018 | 209.5 |
| 528 | Germany | 2018 | 161.6 |
| 551 | Israel | 2018 | 129.9 |
| 560 | Australia | 2018 | 228.8 |
| 562 | China | 2018 | 96.4 |
| 563 | India | 2018 | 24.5 |
| 567 | New Zealand | 2018 | 191.1 |
| 575 | South Africa | 2018 | 88.2 |
| 578 | United States | 2019 | 288.4 |
| 580 | Brazil | 2019 | 58.9 |
| 590 | Finland | 2019 | 203.4 |
| 592 | Germany | 2019 | 156.3 |
| 615 | Israel | 2019 | 132.5 |
| 624 | Australia | 2019 | 233.2 |
| 626 | China | 2019 | 99.1 |
| 627 | India | 2019 | 24.8 |
| 631 | New Zealand | 2019 | 194.4 |
| 639 | South Africa | 2019 | 88.9 |
| 642 | United States | 2020 | 265.2 |
| 644 | Brazil | 2020 | 56.5 |
| 654 | Finland | 2020 | 197.9 |
| 656 | Germany | 2020 | 144.6 |
| 679 | Israel | 2020 | 121.0 |
| 688 | Australia | 2020 | 218.4 |
| 690 | China | 2020 | 101.1 |
| 691 | India | 2020 | 23.2 |
| 695 | New Zealand | 2020 | 174.3 |
| 703 | South Africa | 2020 | 82.7 |
print(filtered_energy2010to2020.dtypes)
Country_name object year int32 Energy_consumption_per_capita float64 dtype: object
filtered_worldbank_gdp = worldbank_gdp[(worldbank_gdp['Country_name'].isin(["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"])) &
(worldbank_gdp['year'].between(2010, 2020))]
filtered_worldbank_gdp = filtered_worldbank_gdp[['Country_name', 'year', 'GDP_per_capita']]
filtered_worldbank_gdp
| Country_name | year | GDP_per_capita | |
|---|---|---|---|
| 649 | Australia | 2020 | 51868.247557 |
| 650 | Australia | 2019 | 55049.571920 |
| 651 | Australia | 2018 | 57273.520475 |
| 652 | Australia | 2017 | 53954.553495 |
| 653 | Australia | 2016 | 49918.793933 |
| 654 | Australia | 2015 | 56758.869203 |
| 655 | Australia | 2014 | 62558.243879 |
| 656 | Australia | 2013 | 68198.419345 |
| 657 | Australia | 2012 | 68078.044228 |
| 658 | Australia | 2011 | 62609.660716 |
| 659 | Australia | 2010 | 52147.024194 |
| 825 | Brazil | 2020 | 6923.699912 |
| 826 | Brazil | 2019 | 8845.324149 |
| 827 | Brazil | 2018 | 9121.020995 |
| 828 | Brazil | 2017 | 9896.718895 |
| 829 | Brazil | 2016 | 8680.736469 |
| 830 | Brazil | 2015 | 8783.215424 |
| 831 | Brazil | 2014 | 12071.404464 |
| 832 | Brazil | 2013 | 12258.565709 |
| 833 | Brazil | 2012 | 12327.513101 |
| 834 | Brazil | 2011 | 13200.556235 |
| 835 | Brazil | 2010 | 11249.291890 |
| 990 | China | 2020 | 10408.719554 |
| 991 | China | 2019 | 10143.860221 |
| 992 | China | 2018 | 9905.406383 |
| 993 | China | 2017 | 8817.045608 |
| 994 | China | 2016 | 8094.390167 |
| 995 | China | 2015 | 8016.445595 |
| 996 | China | 2014 | 7636.074340 |
| 997 | China | 2013 | 7020.386074 |
| 998 | China | 2012 | 6300.582180 |
| 999 | China | 2011 | 5614.386022 |
| 1000 | China | 2010 | 4550.473944 |
| 1276 | Finland | 2020 | 49169.719339 |
| 1277 | Finland | 2019 | 48629.858228 |
| 1278 | Finland | 2018 | 49987.626158 |
| 1279 | Finland | 2017 | 46412.136478 |
| 1280 | Finland | 2016 | 43814.026506 |
| 1281 | Finland | 2015 | 42801.908117 |
| 1282 | Finland | 2014 | 50327.240290 |
| 1283 | Finland | 2013 | 49892.223363 |
| 1284 | Finland | 2012 | 47708.061278 |
| 1285 | Finland | 2011 | 51148.931637 |
| 1286 | Finland | 2010 | 46505.303179 |
| 1342 | Germany | 2020 | 46749.476228 |
| 1343 | Germany | 2019 | 46805.138433 |
| 1344 | Germany | 2018 | 47939.278288 |
| 1345 | Germany | 2017 | 44652.589172 |
| 1346 | Germany | 2016 | 42136.120791 |
| 1347 | Germany | 2015 | 41103.256436 |
| 1348 | Germany | 2014 | 48023.869985 |
| 1349 | Germany | 2013 | 46298.922918 |
| 1350 | Germany | 2012 | 43855.854466 |
| 1351 | Germany | 2011 | 46705.895796 |
| 1352 | Germany | 2010 | 41572.455948 |
| 1518 | India | 2020 | 1913.219733 |
| 1519 | India | 2019 | 2050.163800 |
| 1520 | India | 2018 | 1974.377731 |
| 1521 | India | 2017 | 1957.969813 |
| 1522 | India | 2016 | 1714.279537 |
| 1523 | India | 2015 | 1590.174331 |
| 1524 | India | 2014 | 1559.863779 |
| 1525 | India | 2013 | 1438.057005 |
| 1526 | India | 2012 | 1434.017987 |
| 1527 | India | 2011 | 1449.603301 |
| 1528 | India | 2010 | 1350.634470 |
| 1584 | Israel | 2020 | 44846.791595 |
| 1585 | Israel | 2019 | 44452.232562 |
| 1586 | Israel | 2018 | 42406.845426 |
| 1587 | Israel | 2017 | 41114.781708 |
| 1588 | Israel | 2016 | 37690.473951 |
| 1589 | Israel | 2015 | 36206.522217 |
| 1590 | Israel | 2014 | 38259.681096 |
| 1591 | Israel | 2013 | 36941.842357 |
| 1592 | Israel | 2012 | 33156.228316 |
| 1593 | Israel | 2011 | 34354.716118 |
| 1594 | Israel | 2010 | 31266.605317 |
| 2090 | New Zealand | 2020 | 41760.594784 |
| 2091 | New Zealand | 2019 | 42796.430582 |
| 2092 | New Zealand | 2018 | 43236.886692 |
| 2093 | New Zealand | 2017 | 42910.972836 |
| 2094 | New Zealand | 2016 | 40058.196162 |
| 2095 | New Zealand | 2015 | 38630.726589 |
| 2096 | New Zealand | 2014 | 44572.898754 |
| 2097 | New Zealand | 2013 | 42976.649588 |
| 2098 | New Zealand | 2012 | 39973.380759 |
| 2099 | New Zealand | 2011 | 38387.627078 |
| 2100 | New Zealand | 2010 | 33676.774124 |
| 2486 | South Africa | 2020 | 5753.066494 |
| 2487 | South Africa | 2019 | 6702.526617 |
| 2488 | South Africa | 2018 | 7067.724165 |
| 2489 | South Africa | 2017 | 6734.475153 |
| 2490 | South Africa | 2016 | 5735.066787 |
| 2491 | South Africa | 2015 | 6204.929901 |
| 2492 | South Africa | 2014 | 6965.137897 |
| 2493 | South Africa | 2013 | 7441.230854 |
| 2494 | South Africa | 2012 | 8173.869138 |
| 2495 | South Africa | 2011 | 8737.041269 |
| 2496 | South Africa | 2010 | 8059.562798 |
| 2805 | United States | 2020 | 63528.634303 |
| 2806 | United States | 2019 | 65120.394663 |
| 2807 | United States | 2018 | 62823.309438 |
| 2808 | United States | 2017 | 59907.754261 |
| 2809 | United States | 2016 | 57866.744934 |
| 2810 | United States | 2015 | 56762.729452 |
| 2811 | United States | 2014 | 55123.849787 |
| 2812 | United States | 2013 | 53291.127689 |
| 2813 | United States | 2012 | 51784.418574 |
| 2814 | United States | 2011 | 50065.966504 |
| 2815 | United States | 2010 | 48650.643128 |
print(filtered_worldbank_gdp.dtypes)
Country_name object year int32 GDP_per_capita float64 dtype: object
filtered_worldbank_CO2 = worldbank_CO2[(worldbank_CO2['Country_name'].isin(["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"])) &
(worldbank_CO2['year'].between(2010, 2020))]
filtered_worldbank_CO2 = filtered_worldbank_CO2[['Country_name', 'year', 'CO2_per_capita']]
filtered_worldbank_CO2
| Country_name | year | CO2_per_capita | |
|---|---|---|---|
| 649 | Australia | 2020 | 14.776137 |
| 650 | Australia | 2019 | 15.599045 |
| 651 | Australia | 2018 | 15.865714 |
| 652 | Australia | 2017 | 16.149150 |
| 653 | Australia | 2016 | 16.320331 |
| 654 | Australia | 2015 | 16.198458 |
| 655 | Australia | 2014 | 16.155745 |
| 656 | Australia | 2013 | 16.794588 |
| 657 | Australia | 2012 | 17.405618 |
| 658 | Australia | 2011 | 17.656055 |
| 659 | Australia | 2010 | 17.973752 |
| 825 | Brazil | 2020 | 1.942523 |
| 826 | Brazil | 2019 | 2.050770 |
| 827 | Brazil | 2018 | 2.064261 |
| 828 | Brazil | 2017 | 2.185487 |
| 829 | Brazil | 2016 | 2.161260 |
| 830 | Brazil | 2015 | 2.365361 |
| 831 | Brazil | 2014 | 2.514592 |
| 832 | Brazil | 2013 | 2.413447 |
| 833 | Brazil | 2012 | 2.271418 |
| 834 | Brazil | 2011 | 2.110628 |
| 835 | Brazil | 2010 | 2.026606 |
| 990 | China | 2020 | 7.756138 |
| 991 | China | 2019 | 7.645436 |
| 992 | China | 2018 | 7.533193 |
| 993 | China | 2017 | 7.226160 |
| 994 | China | 2016 | 7.105480 |
| 995 | China | 2015 | 7.145132 |
| 996 | China | 2014 | 7.304713 |
| 997 | China | 2013 | 7.320155 |
| 998 | China | 2012 | 7.045200 |
| 999 | China | 2011 | 6.901347 |
| 1000 | China | 2010 | 6.335420 |
| 1276 | Finland | 2020 | 6.570145 |
| 1277 | Finland | 2019 | 7.423040 |
| 1278 | Finland | 2018 | 8.049188 |
| 1279 | Finland | 2017 | 7.809319 |
| 1280 | Finland | 2016 | 8.316248 |
| 1281 | Finland | 2015 | 7.813698 |
| 1282 | Finland | 2014 | 8.452183 |
| 1283 | Finland | 2013 | 9.228086 |
| 1284 | Finland | 2012 | 9.126037 |
| 1285 | Finland | 2011 | 10.230256 |
| 1286 | Finland | 2010 | 11.658082 |
| 1342 | Germany | 2020 | 7.255221 |
| 1343 | Germany | 2019 | 7.927188 |
| 1344 | Germany | 2018 | 8.537043 |
| 1345 | Germany | 2017 | 8.858345 |
| 1346 | Germany | 2016 | 9.072972 |
| 1347 | Germany | 2015 | 9.087345 |
| 1348 | Germany | 2014 | 9.088528 |
| 1349 | Germany | 2013 | 9.624229 |
| 1350 | Germany | 2012 | 9.451289 |
| 1351 | Germany | 2011 | 9.299003 |
| 1352 | Germany | 2010 | 9.453389 |
| 1518 | India | 2020 | 1.576093 |
| 1519 | India | 2019 | 1.752534 |
| 1520 | India | 2018 | 1.795595 |
| 1521 | India | 2017 | 1.704927 |
| 1522 | India | 2016 | 1.639914 |
| 1523 | India | 2015 | 1.631323 |
| 1524 | India | 2014 | 1.642465 |
| 1525 | India | 2013 | 1.527674 |
| 1526 | India | 2012 | 1.498204 |
| 1527 | India | 2011 | 1.396878 |
| 1528 | India | 2010 | 1.338034 |
| 1584 | Israel | 2020 | 6.345216 |
| 1585 | Israel | 2019 | 6.935752 |
| 1586 | Israel | 2018 | 6.914993 |
| 1587 | Israel | 2017 | 7.563874 |
| 1588 | Israel | 2016 | 7.633162 |
| 1589 | Israel | 2015 | 7.913354 |
| 1590 | Israel | 2014 | 7.877332 |
| 1591 | Israel | 2013 | 8.313481 |
| 1592 | Israel | 2012 | 9.615473 |
| 1593 | Israel | 2011 | 8.991063 |
| 1594 | Israel | 2010 | 9.250262 |
| 2090 | New Zealand | 2020 | 6.160799 |
| 2091 | New Zealand | 2019 | 6.830053 |
| 2092 | New Zealand | 2018 | 6.613272 |
| 2093 | New Zealand | 2017 | 6.840494 |
| 2094 | New Zealand | 2016 | 6.615409 |
| 2095 | New Zealand | 2015 | 7.003341 |
| 2096 | New Zealand | 2014 | 7.078645 |
| 2097 | New Zealand | 2013 | 7.178024 |
| 2098 | New Zealand | 2012 | 7.283728 |
| 2099 | New Zealand | 2011 | 6.909352 |
| 2100 | New Zealand | 2010 | 7.136622 |
| 2486 | South Africa | 2020 | 6.687563 |
| 2487 | South Africa | 2019 | 7.688908 |
| 2488 | South Africa | 2018 | 7.667377 |
| 2489 | South Africa | 2017 | 7.683708 |
| 2490 | South Africa | 2016 | 7.544590 |
| 2491 | South Africa | 2015 | 7.607189 |
| 2492 | South Africa | 2014 | 8.191153 |
| 2493 | South Africa | 2013 | 8.116435 |
| 2494 | South Africa | 2012 | 8.034649 |
| 2495 | South Africa | 2011 | 7.808054 |
| 2496 | South Africa | 2010 | 8.217612 |
| 2805 | United States | 2020 | 13.032828 |
| 2806 | United States | 2019 | 14.673381 |
| 2807 | United States | 2018 | 15.222518 |
| 2808 | United States | 2017 | 14.823245 |
| 2809 | United States | 2016 | 15.149883 |
| 2810 | United States | 2015 | 15.560015 |
| 2811 | United States | 2014 | 16.040917 |
| 2812 | United States | 2013 | 16.111175 |
| 2813 | United States | 2012 | 15.789760 |
| 2814 | United States | 2011 | 16.604190 |
| 2815 | United States | 2010 | 17.431737 |
print(filtered_worldbank_CO2.dtypes)
Country_name object year int32 CO2_per_capita float64 dtype: object
filtered_worldbank_forest = worldbank_forest[(worldbank_forest['Country_name'].isin(["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"])) &
(worldbank_forest['year'].between(2010, 2020))]
filtered_worldbank_forest = filtered_worldbank_forest[['Country_name', 'year', 'ForestArea']]
filtered_worldbank_forest
| Country_name | year | ForestArea | |
|---|---|---|---|
| 649 | Australia | 2020 | 1340051.00 |
| 650 | Australia | 2019 | 1340051.00 |
| 651 | Australia | 2018 | 1340051.00 |
| 652 | Australia | 2017 | 1340174.00 |
| 653 | Australia | 2016 | 1340372.00 |
| 654 | Australia | 2015 | 1330945.00 |
| 655 | Australia | 2014 | 1323848.20 |
| 656 | Australia | 2013 | 1316751.40 |
| 657 | Australia | 2012 | 1309654.60 |
| 658 | Australia | 2011 | 1302557.80 |
| 659 | Australia | 2010 | 1295461.00 |
| 825 | Brazil | 2020 | 4966196.00 |
| 826 | Brazil | 2019 | 4977985.00 |
| 827 | Brazil | 2018 | 4990514.00 |
| 828 | Brazil | 2017 | 5000916.00 |
| 829 | Brazil | 2016 | 5020821.00 |
| 830 | Brazil | 2015 | 5038848.00 |
| 831 | Brazil | 2014 | 5054239.80 |
| 832 | Brazil | 2013 | 5069631.60 |
| 833 | Brazil | 2012 | 5085023.40 |
| 834 | Brazil | 2011 | 5100415.20 |
| 835 | Brazil | 2010 | 5115807.00 |
| 990 | China | 2020 | 2199781.80 |
| 991 | China | 2019 | 2180986.10 |
| 992 | China | 2018 | 2162190.40 |
| 993 | China | 2017 | 2143394.70 |
| 994 | China | 2016 | 2124598.67 |
| 995 | China | 2015 | 2102942.50 |
| 996 | China | 2014 | 2083574.76 |
| 997 | China | 2013 | 2064207.02 |
| 998 | China | 2012 | 2044839.28 |
| 999 | China | 2011 | 2025471.54 |
| 1000 | China | 2010 | 2006103.80 |
| 1276 | Finland | 2020 | 224090.00 |
| 1277 | Finland | 2019 | 224090.00 |
| 1278 | Finland | 2018 | 224090.00 |
| 1279 | Finland | 2017 | 224090.00 |
| 1280 | Finland | 2016 | 224090.00 |
| 1281 | Finland | 2015 | 224090.00 |
| 1282 | Finland | 2014 | 223756.00 |
| 1283 | Finland | 2013 | 223422.00 |
| 1284 | Finland | 2012 | 223088.00 |
| 1285 | Finland | 2011 | 222754.00 |
| 1286 | Finland | 2010 | 222420.00 |
| 1342 | Germany | 2020 | 114190.00 |
| 1343 | Germany | 2019 | 114190.00 |
| 1344 | Germany | 2018 | 114190.00 |
| 1345 | Germany | 2017 | 114190.00 |
| 1346 | Germany | 2016 | 114190.00 |
| 1347 | Germany | 2015 | 114190.00 |
| 1348 | Germany | 2014 | 114170.00 |
| 1349 | Germany | 2013 | 114150.00 |
| 1350 | Germany | 2012 | 114130.00 |
| 1351 | Germany | 2011 | 114110.00 |
| 1352 | Germany | 2010 | 114090.00 |
| 1518 | India | 2020 | 721600.00 |
| 1519 | India | 2019 | 718936.00 |
| 1520 | India | 2018 | 716272.00 |
| 1521 | India | 2017 | 713608.00 |
| 1522 | India | 2016 | 710944.00 |
| 1523 | India | 2015 | 708280.00 |
| 1524 | India | 2014 | 705616.00 |
| 1525 | India | 2013 | 702952.00 |
| 1526 | India | 2012 | 700288.00 |
| 1527 | India | 2011 | 697624.00 |
| 1528 | India | 2010 | 694960.00 |
| 1584 | Israel | 2020 | 1400.00 |
| 1585 | Israel | 2019 | 1400.00 |
| 1586 | Israel | 2018 | 1400.00 |
| 1587 | Israel | 2017 | 1400.00 |
| 1588 | Israel | 2016 | 1400.00 |
| 1589 | Israel | 2015 | 1650.00 |
| 1590 | Israel | 2014 | 1628.00 |
| 1591 | Israel | 2013 | 1606.00 |
| 1592 | Israel | 2012 | 1584.00 |
| 1593 | Israel | 2011 | 1562.00 |
| 1594 | Israel | 2010 | 1540.00 |
| 2090 | New Zealand | 2020 | 98925.90 |
| 2091 | New Zealand | 2019 | 98655.20 |
| 2092 | New Zealand | 2018 | 98551.50 |
| 2093 | New Zealand | 2017 | 98508.50 |
| 2094 | New Zealand | 2016 | 98467.50 |
| 2095 | New Zealand | 2015 | 98466.10 |
| 2096 | New Zealand | 2014 | 98469.12 |
| 2097 | New Zealand | 2013 | 98472.14 |
| 2098 | New Zealand | 2012 | 98475.16 |
| 2099 | New Zealand | 2011 | 98478.18 |
| 2100 | New Zealand | 2010 | 98481.20 |
| 2486 | South Africa | 2020 | 170500.90 |
| 2487 | South Africa | 2019 | 170864.90 |
| 2488 | South Africa | 2018 | 171228.90 |
| 2489 | South Africa | 2017 | 171592.90 |
| 2490 | South Africa | 2016 | 171956.90 |
| 2491 | South Africa | 2015 | 172320.90 |
| 2492 | South Africa | 2014 | 172684.90 |
| 2493 | South Africa | 2013 | 173048.90 |
| 2494 | South Africa | 2012 | 173412.90 |
| 2495 | South Africa | 2011 | 173776.90 |
| 2496 | South Africa | 2010 | 174140.90 |
| 2805 | United States | 2020 | 3097950.00 |
| 2806 | United States | 2019 | 3097950.00 |
| 2807 | United States | 2018 | 3097950.00 |
| 2808 | United States | 2017 | 3097950.00 |
| 2809 | United States | 2016 | 3100950.00 |
| 2810 | United States | 2015 | 3100950.00 |
| 2811 | United States | 2014 | 3098200.00 |
| 2812 | United States | 2013 | 3095450.00 |
| 2813 | United States | 2012 | 3092700.00 |
| 2814 | United States | 2011 | 3089950.00 |
| 2815 | United States | 2010 | 3087200.00 |
print(filtered_worldbank_forest.dtypes)
Country_name object year int32 ForestArea float64 dtype: object
filtered_happiness = happiness[(happiness['Country_name'].isin(["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"])) &
(happiness['year'].between(2010, 2020))]
filtered_happiness = filtered_happiness[['Country_name', 'year', 'Life_ladder']]
filtered_happiness['year'] = filtered_happiness['year'].astype('int32')
print(filtered_happiness)
Country_name year Life_ladder 69 Australia 2010 7.450047 70 Australia 2011 7.405616 71 Australia 2012 7.195586 72 Australia 2013 7.364169 73 Australia 2014 7.288550 74 Australia 2015 7.309061 75 Australia 2016 7.250080 76 Australia 2017 7.257038 77 Australia 2018 7.176993 78 Australia 2019 7.233995 79 Australia 2020 7.137368 222 Brazil 2010 6.837331 223 Brazil 2011 7.037817 224 Brazil 2012 6.660004 225 Brazil 2013 7.140283 226 Brazil 2014 6.980999 227 Brazil 2015 6.546897 228 Brazil 2016 6.374817 229 Brazil 2017 6.332929 230 Brazil 2018 6.190922 231 Brazil 2019 6.451149 232 Brazil 2020 6.109718 346 China 2010 4.652737 347 China 2011 5.037208 348 China 2012 5.094917 349 China 2013 5.241090 350 China 2014 5.195619 351 China 2015 5.303878 352 China 2016 5.324956 353 China 2017 5.099061 354 China 2018 5.131434 355 China 2019 5.144120 356 China 2020 5.771065 553 Finland 2010 7.393264 554 Finland 2011 7.354225 555 Finland 2012 7.420209 556 Finland 2013 7.444636 557 Finland 2014 7.384571 558 Finland 2015 7.447926 559 Finland 2016 7.659843 560 Finland 2017 7.788252 561 Finland 2018 7.858107 562 Finland 2019 7.780348 563 Finland 2020 7.889350 610 Germany 2010 6.724531 611 Germany 2011 6.621312 612 Germany 2012 6.702362 613 Germany 2013 6.965125 614 Germany 2014 6.984214 615 Germany 2015 7.037138 616 Germany 2016 6.873763 617 Germany 2017 7.074325 618 Germany 2018 7.118364 619 Germany 2019 7.035472 620 Germany 2020 7.311898 736 India 2010 4.989277 737 India 2011 4.634871 738 India 2012 4.720147 739 India 2013 4.427789 740 India 2014 4.424379 741 India 2015 4.342079 742 India 2016 4.179177 743 India 2017 4.046111 744 India 2018 3.818069 745 India 2019 3.248770 746 India 2020 4.225281 804 Israel 2010 7.358916 805 Israel 2011 7.433148 806 Israel 2012 7.110855 807 Israel 2013 7.320563 808 Israel 2014 7.400570 809 Israel 2015 7.079411 810 Israel 2016 7.159011 811 Israel 2017 7.331036 812 Israel 2018 6.927179 813 Israel 2019 7.331780 814 Israel 2020 7.194928 1228 New Zealand 2010 7.223756 1229 New Zealand 2011 7.190638 1230 New Zealand 2012 7.249630 1231 New Zealand 2013 7.280152 1232 New Zealand 2014 7.305892 1233 New Zealand 2015 7.418121 1234 New Zealand 2016 7.225688 1235 New Zealand 2017 7.327183 1236 New Zealand 2018 7.370286 1237 New Zealand 2019 7.205174 1238 New Zealand 2020 7.257382 1570 South Africa 2010 4.652429 1571 South Africa 2011 4.930511 1572 South Africa 2012 5.133888 1573 South Africa 2013 3.660727 1574 South Africa 2014 4.828456 1575 South Africa 2015 4.887326 1576 South Africa 2016 4.769740 1577 South Africa 2017 4.513655 1578 South Africa 2018 4.883922 1579 South Africa 2019 5.034863 1580 South Africa 2020 4.946801 1840 United States 2010 7.163616 1841 United States 2011 7.115139 1842 United States 2012 7.026227 1843 United States 2013 7.249285 1844 United States 2014 7.151114 1845 United States 2015 6.863947 1846 United States 2016 6.803600 1847 United States 2017 6.991759 1848 United States 2018 6.882685 1849 United States 2019 6.943701 1850 United States 2020 7.028088
print(filtered_happiness.dtypes)
Country_name object year int32 Life_ladder float64 dtype: object
filtered_worldbank_population = worldbank_population[(worldbank_population['Country_name'].isin(["Australia", "New Zealand", "United States", "Brazil", "Germany",
"Finland", "South Africa", "Israel", "China", "India"])) &
(worldbank_population['year'].between(2010, 2020))]
filtered_worldbank_population = filtered_worldbank_population[['Country_name', 'year', 'Population']]
filtered_worldbank_population
| Country_name | year | Population | |
|---|---|---|---|
| 649 | Australia | 2020 | 2.564925e+07 |
| 650 | Australia | 2019 | 2.533483e+07 |
| 651 | Australia | 2018 | 2.496326e+07 |
| 652 | Australia | 2017 | 2.459259e+07 |
| 653 | Australia | 2016 | 2.419091e+07 |
| 654 | Australia | 2015 | 2.381600e+07 |
| 655 | Australia | 2014 | 2.347569e+07 |
| 656 | Australia | 2013 | 2.312813e+07 |
| 657 | Australia | 2012 | 2.273346e+07 |
| 658 | Australia | 2011 | 2.234002e+07 |
| 659 | Australia | 2010 | 2.203175e+07 |
| 825 | Brazil | 2020 | 2.131963e+08 |
| 826 | Brazil | 2019 | 2.117829e+08 |
| 827 | Brazil | 2018 | 2.101666e+08 |
| 828 | Brazil | 2017 | 2.085050e+08 |
| 829 | Brazil | 2016 | 2.068596e+08 |
| 830 | Brazil | 2015 | 2.051882e+08 |
| 831 | Brazil | 2014 | 2.034596e+08 |
| 832 | Brazil | 2013 | 2.017218e+08 |
| 833 | Brazil | 2012 | 1.999777e+08 |
| 834 | Brazil | 2011 | 1.981853e+08 |
| 835 | Brazil | 2010 | 1.963535e+08 |
| 990 | China | 2020 | 1.411100e+09 |
| 991 | China | 2019 | 1.407745e+09 |
| 992 | China | 2018 | 1.402760e+09 |
| 993 | China | 2017 | 1.396215e+09 |
| 994 | China | 2016 | 1.387790e+09 |
| 995 | China | 2015 | 1.379860e+09 |
| 996 | China | 2014 | 1.371860e+09 |
| 997 | China | 2013 | 1.363240e+09 |
| 998 | China | 2012 | 1.354190e+09 |
| 999 | China | 2011 | 1.345035e+09 |
| 1000 | China | 2010 | 1.337705e+09 |
| 1276 | Finland | 2020 | 5.529543e+06 |
| 1277 | Finland | 2019 | 5.521606e+06 |
| 1278 | Finland | 2018 | 5.515525e+06 |
| 1279 | Finland | 2017 | 5.508214e+06 |
| 1280 | Finland | 2016 | 5.495303e+06 |
| 1281 | Finland | 2015 | 5.479531e+06 |
| 1282 | Finland | 2014 | 5.461512e+06 |
| 1283 | Finland | 2013 | 5.438972e+06 |
| 1284 | Finland | 2012 | 5.413971e+06 |
| 1285 | Finland | 2011 | 5.388272e+06 |
| 1286 | Finland | 2010 | 5.363352e+06 |
| 1342 | Germany | 2020 | 8.316087e+07 |
| 1343 | Germany | 2019 | 8.309296e+07 |
| 1344 | Germany | 2018 | 8.290578e+07 |
| 1345 | Germany | 2017 | 8.265700e+07 |
| 1346 | Germany | 2016 | 8.234867e+07 |
| 1347 | Germany | 2015 | 8.168661e+07 |
| 1348 | Germany | 2014 | 8.098250e+07 |
| 1349 | Germany | 2013 | 8.064560e+07 |
| 1350 | Germany | 2012 | 8.042582e+07 |
| 1351 | Germany | 2011 | 8.027498e+07 |
| 1352 | Germany | 2010 | 8.177693e+07 |
| 1518 | India | 2020 | 1.396387e+09 |
| 1519 | India | 2019 | 1.383112e+09 |
| 1520 | India | 2018 | 1.369003e+09 |
| 1521 | India | 2017 | 1.354196e+09 |
| 1522 | India | 2016 | 1.338636e+09 |
| 1523 | India | 2015 | 1.322867e+09 |
| 1524 | India | 2014 | 1.307247e+09 |
| 1525 | India | 2013 | 1.291132e+09 |
| 1526 | India | 2012 | 1.274487e+09 |
| 1527 | India | 2011 | 1.257621e+09 |
| 1528 | India | 2010 | 1.240614e+09 |
| 1584 | Israel | 2020 | 9.215100e+06 |
| 1585 | Israel | 2019 | 9.054000e+06 |
| 1586 | Israel | 2018 | 8.882800e+06 |
| 1587 | Israel | 2017 | 8.713300e+06 |
| 1588 | Israel | 2016 | 8.546000e+06 |
| 1589 | Israel | 2015 | 8.380100e+06 |
| 1590 | Israel | 2014 | 8.215700e+06 |
| 1591 | Israel | 2013 | 8.059500e+06 |
| 1592 | Israel | 2012 | 7.910500e+06 |
| 1593 | Israel | 2011 | 7.765800e+06 |
| 1594 | Israel | 2010 | 7.623600e+06 |
| 2090 | New Zealand | 2020 | 5.090200e+06 |
| 2091 | New Zealand | 2019 | 4.979200e+06 |
| 2092 | New Zealand | 2018 | 4.900600e+06 |
| 2093 | New Zealand | 2017 | 4.813600e+06 |
| 2094 | New Zealand | 2016 | 4.714100e+06 |
| 2095 | New Zealand | 2015 | 4.609400e+06 |
| 2096 | New Zealand | 2014 | 4.516500e+06 |
| 2097 | New Zealand | 2013 | 4.442100e+06 |
| 2098 | New Zealand | 2012 | 4.408100e+06 |
| 2099 | New Zealand | 2011 | 4.384000e+06 |
| 2100 | New Zealand | 2010 | 4.350700e+06 |
| 2486 | South Africa | 2020 | 5.880193e+07 |
| 2487 | South Africa | 2019 | 5.808706e+07 |
| 2488 | South Africa | 2018 | 5.733964e+07 |
| 2489 | South Africa | 2017 | 5.664121e+07 |
| 2490 | South Africa | 2016 | 5.642227e+07 |
| 2491 | South Africa | 2015 | 5.587650e+07 |
| 2492 | South Africa | 2014 | 5.472955e+07 |
| 2493 | South Africa | 2013 | 5.387362e+07 |
| 2494 | South Africa | 2012 | 5.314503e+07 |
| 2495 | South Africa | 2011 | 5.244332e+07 |
| 2496 | South Africa | 2010 | 5.178492e+07 |
| 2805 | United States | 2020 | 3.315115e+08 |
| 2806 | United States | 2019 | 3.283300e+08 |
| 2807 | United States | 2018 | 3.268382e+08 |
| 2808 | United States | 2017 | 3.251221e+08 |
| 2809 | United States | 2016 | 3.230718e+08 |
| 2810 | United States | 2015 | 3.207390e+08 |
| 2811 | United States | 2014 | 3.183863e+08 |
| 2812 | United States | 2013 | 3.160599e+08 |
| 2813 | United States | 2012 | 3.138777e+08 |
| 2814 | United States | 2011 | 3.115835e+08 |
| 2815 | United States | 2010 | 3.093271e+08 |
print(filtered_worldbank_population.dtypes)
Country_name object year int32 Population float64 dtype: object
merged_data = pd.merge(filtered_energy2010to2020, filtered_worldbank_gdp,on=['Country_name', 'year'])
merged_data = pd.merge(merged_data, filtered_worldbank_CO2,on=['Country_name', 'year'])
merged_data = pd.merge(merged_data, filtered_worldbank_forest, on=['Country_name', 'year'])
merged_data = pd.merge(merged_data, filtered_happiness, on=['Country_name', 'year'])
merged_data = pd.merge(merged_data, filtered_worldbank_population, on=['Country_name', 'year'])
merged_data
| Country_name | year | Energy_consumption_per_capita | GDP_per_capita | CO2_per_capita | ForestArea | Life_ladder | Population | |
|---|---|---|---|---|---|---|---|---|
| 0 | United States | 2010 | 300.7 | 48650.643128 | 17.431737 | 3087200.00 | 7.163616 | 3.093271e+08 |
| 1 | Brazil | 2010 | 56.0 | 11249.291890 | 2.026606 | 5115807.00 | 6.837331 | 1.963535e+08 |
| 2 | Finland | 2010 | 242.8 | 46505.303179 | 11.658082 | 222420.00 | 7.393264 | 5.363352e+06 |
| 3 | Germany | 2010 | 169.6 | 41572.455948 | 9.453389 | 114090.00 | 6.724531 | 8.177693e+07 |
| 4 | Israel | 2010 | 135.0 | 31266.605317 | 9.250262 | 1540.00 | 7.358916 | 7.623600e+06 |
| 5 | Australia | 2010 | 240.5 | 52147.024194 | 17.973752 | 1295461.00 | 7.450047 | 2.203175e+07 |
| 6 | China | 2010 | 76.2 | 4550.473944 | 6.335420 | 2006103.80 | 4.652737 | 1.337705e+09 |
| 7 | India | 2010 | 18.2 | 1350.634470 | 1.338034 | 694960.00 | 4.989277 | 1.240614e+09 |
| 8 | New Zealand | 2010 | 188.9 | 33676.774124 | 7.136622 | 98481.20 | 7.223756 | 4.350700e+06 |
| 9 | South Africa | 2010 | 102.7 | 8059.562798 | 8.217612 | 174140.90 | 4.652429 | 5.178492e+07 |
| 10 | United States | 2011 | 295.4 | 50065.966504 | 16.604190 | 3089950.00 | 7.115139 | 3.115835e+08 |
| 11 | Brazil | 2011 | 58.0 | 13200.556235 | 2.110628 | 5100415.20 | 7.037817 | 1.981853e+08 |
| 12 | Finland | 2011 | 225.8 | 51148.931637 | 10.230256 | 222754.00 | 7.354225 | 5.388272e+06 |
| 13 | Germany | 2011 | 163.3 | 46705.895796 | 9.299003 | 114110.00 | 6.621312 | 8.027498e+07 |
| 14 | Israel | 2011 | 135.6 | 34354.716118 | 8.991063 | 1562.00 | 7.433148 | 7.765800e+06 |
| 15 | Australia | 2011 | 243.3 | 62609.660716 | 17.656055 | 1302557.80 | 7.405616 | 2.234002e+07 |
| 16 | China | 2011 | 81.8 | 5614.386022 | 6.901347 | 2025471.54 | 5.037208 | 1.345035e+09 |
| 17 | India | 2011 | 19.0 | 1449.603301 | 1.396878 | 697624.00 | 4.634871 | 1.257621e+09 |
| 18 | New Zealand | 2011 | 187.9 | 38387.627078 | 6.909352 | 98478.18 | 7.190638 | 4.384000e+06 |
| 19 | South Africa | 2011 | 99.9 | 8737.041269 | 7.808054 | 173776.90 | 4.930511 | 5.244332e+07 |
| 20 | United States | 2012 | 285.4 | 51784.418574 | 15.789760 | 3092700.00 | 7.026227 | 3.138777e+08 |
| 21 | Brazil | 2012 | 58.5 | 12327.513101 | 2.271418 | 5085023.40 | 6.660004 | 1.999777e+08 |
| 22 | Finland | 2012 | 218.5 | 47708.061278 | 9.126037 | 223088.00 | 7.420209 | 5.413971e+06 |
| 23 | Germany | 2012 | 165.1 | 43855.854466 | 9.451289 | 114130.00 | 6.702362 | 8.042582e+07 |
| 24 | Israel | 2012 | 139.3 | 33156.228316 | 9.615473 | 1584.00 | 7.110855 | 7.910500e+06 |
| 25 | Australia | 2012 | 236.5 | 68078.044228 | 17.405618 | 1309654.60 | 7.195586 | 2.273346e+07 |
| 26 | China | 2012 | 84.6 | 6300.582180 | 7.045200 | 2044839.28 | 5.094917 | 1.354190e+09 |
| 27 | India | 2012 | 19.8 | 1434.017987 | 1.498204 | 700288.00 | 4.720147 | 1.274487e+09 |
| 28 | New Zealand | 2012 | 187.1 | 39973.380759 | 7.283728 | 98475.16 | 7.249630 | 4.408100e+06 |
| 29 | South Africa | 2012 | 96.9 | 8173.869138 | 8.034649 | 173412.90 | 5.133888 | 5.314503e+07 |
| 30 | United States | 2013 | 290.9 | 53291.127689 | 16.111175 | 3095450.00 | 7.249285 | 3.160599e+08 |
| 31 | Brazil | 2013 | 60.2 | 12258.565709 | 2.413447 | 5069631.60 | 7.140283 | 2.017218e+08 |
| 32 | Finland | 2013 | 218.8 | 49892.223363 | 9.228086 | 223422.00 | 7.444636 | 5.438972e+06 |
| 33 | Germany | 2013 | 169.3 | 46298.922918 | 9.624229 | 114150.00 | 6.965125 | 8.064560e+07 |
| 34 | Israel | 2013 | 127.3 | 36941.842357 | 8.313481 | 1606.00 | 7.320563 | 8.059500e+06 |
| 35 | Australia | 2013 | 235.9 | 68198.419345 | 16.794588 | 1316751.40 | 7.364169 | 2.312813e+07 |
| 36 | China | 2013 | 87.2 | 7020.386074 | 7.320155 | 2064207.02 | 5.241090 | 1.363240e+09 |
| 37 | India | 2013 | 20.3 | 1438.057005 | 1.527674 | 702952.00 | 4.427789 | 1.291132e+09 |
| 38 | New Zealand | 2013 | 186.2 | 42976.649588 | 7.178024 | 98472.14 | 7.280152 | 4.442100e+06 |
| 39 | South Africa | 2013 | 95.7 | 7441.230854 | 8.116435 | 173048.90 | 3.660727 | 5.387362e+07 |
| 40 | United States | 2014 | 291.8 | 55123.849787 | 16.040917 | 3098200.00 | 7.151114 | 3.183863e+08 |
| 41 | Brazil | 2014 | 61.1 | 12071.404464 | 2.514592 | 5054239.80 | 6.980999 | 2.034596e+08 |
| 42 | Finland | 2014 | 210.1 | 50327.240290 | 8.452183 | 223756.00 | 7.384571 | 5.461512e+06 |
| 43 | Germany | 2014 | 161.6 | 48023.869985 | 9.088528 | 114170.00 | 6.984214 | 8.098250e+07 |
| 44 | Israel | 2014 | 123.2 | 38259.681096 | 7.877332 | 1628.00 | 7.400570 | 8.215700e+06 |
| 45 | Australia | 2014 | 234.8 | 62558.243879 | 16.155745 | 1323848.20 | 7.288550 | 2.347569e+07 |
| 46 | China | 2014 | 89.2 | 7636.074340 | 7.304713 | 2083574.76 | 5.195619 | 1.371860e+09 |
| 47 | India | 2014 | 21.4 | 1559.863779 | 1.642465 | 705616.00 | 4.424379 | 1.307247e+09 |
| 48 | New Zealand | 2014 | 192.6 | 44572.898754 | 7.078645 | 98469.12 | 7.305892 | 4.516500e+06 |
| 49 | South Africa | 2014 | 95.3 | 6965.137897 | 8.191153 | 172684.90 | 4.828456 | 5.472955e+07 |
| 50 | United States | 2015 | 287.0 | 56762.729452 | 15.560015 | 3100950.00 | 6.863947 | 3.207390e+08 |
| 51 | Brazil | 2015 | 59.7 | 8783.215424 | 2.365361 | 5038848.00 | 6.546897 | 2.051882e+08 |
| 52 | Finland | 2015 | 207.9 | 42801.908117 | 7.813698 | 224090.00 | 7.447926 | 5.479531e+06 |
| 53 | Germany | 2015 | 163.8 | 41103.256436 | 9.087345 | 114190.00 | 7.037138 | 8.168661e+07 |
| 54 | Israel | 2015 | 128.0 | 36206.522217 | 7.913354 | 1650.00 | 7.079411 | 8.380100e+06 |
| 55 | Australia | 2015 | 237.0 | 56758.869203 | 16.198458 | 1330945.00 | 7.309061 | 2.381600e+07 |
| 56 | China | 2015 | 89.9 | 8016.445595 | 7.145132 | 2102942.50 | 5.303878 | 1.379860e+09 |
| 57 | India | 2015 | 21.9 | 1590.174331 | 1.631323 | 708280.00 | 4.342079 | 1.322867e+09 |
| 58 | New Zealand | 2015 | 192.3 | 38630.726589 | 7.003341 | 98466.10 | 7.418121 | 4.609400e+06 |
| 59 | South Africa | 2015 | 91.9 | 6204.929901 | 7.607189 | 172320.90 | 4.887326 | 5.587650e+07 |
| 60 | United States | 2016 | 284.7 | 57866.744934 | 15.149883 | 3100950.00 | 6.803600 | 3.230718e+08 |
| 61 | Brazil | 2016 | 57.7 | 8680.736469 | 2.161260 | 5020821.00 | 6.374817 | 2.068596e+08 |
| 62 | Finland | 2016 | 210.9 | 43814.026506 | 8.316248 | 224090.00 | 7.659843 | 5.495303e+06 |
| 63 | Germany | 2016 | 165.7 | 42136.120791 | 9.072972 | 114190.00 | 6.873763 | 8.234867e+07 |
| 64 | Israel | 2016 | 128.1 | 37690.473951 | 7.633162 | 1400.00 | 7.159011 | 8.546000e+06 |
| 65 | Australia | 2016 | 234.8 | 49918.793933 | 16.320331 | 1340372.00 | 7.250080 | 2.419091e+07 |
| 66 | China | 2016 | 91.0 | 8094.390167 | 7.105480 | 2124598.67 | 5.324956 | 1.387790e+09 |
| 67 | India | 2016 | 22.6 | 1714.279537 | 1.639914 | 710944.00 | 4.179177 | 1.338636e+09 |
| 68 | New Zealand | 2016 | 191.7 | 40058.196162 | 6.615409 | 98467.50 | 7.225688 | 4.714100e+06 |
| 69 | South Africa | 2016 | 94.8 | 5735.066787 | 7.544590 | 171956.90 | 4.769740 | 5.642227e+07 |
| 70 | United States | 2017 | 283.8 | 59907.754261 | 14.823245 | 3097950.00 | 6.991759 | 3.251221e+08 |
| 71 | Brazil | 2017 | 57.9 | 9896.718895 | 2.185487 | 5000916.00 | 6.332929 | 2.085050e+08 |
| 72 | Finland | 2017 | 205.7 | 46412.136478 | 7.809319 | 224090.00 | 7.788252 | 5.508214e+06 |
| 73 | Germany | 2017 | 166.7 | 44652.589172 | 8.858345 | 114190.00 | 7.074325 | 8.265700e+07 |
| 74 | Israel | 2017 | 131.7 | 41114.781708 | 7.563874 | 1400.00 | 7.331036 | 8.713300e+06 |
| 75 | Australia | 2017 | 230.5 | 53954.553495 | 16.149150 | 1340174.00 | 7.257038 | 2.459259e+07 |
| 76 | China | 2017 | 93.5 | 8817.045608 | 7.226160 | 2143394.70 | 5.099061 | 1.396215e+09 |
| 77 | India | 2017 | 23.3 | 1957.969813 | 1.704927 | 713608.00 | 4.046111 | 1.354196e+09 |
| 78 | New Zealand | 2017 | 193.2 | 42910.972836 | 6.840494 | 98508.50 | 7.327183 | 4.813600e+06 |
| 79 | South Africa | 2017 | 92.9 | 6734.475153 | 7.683708 | 171592.90 | 4.513655 | 5.664121e+07 |
| 80 | United States | 2018 | 292.4 | 62823.309438 | 15.222518 | 3097950.00 | 6.882685 | 3.268382e+08 |
| 81 | Brazil | 2018 | 57.8 | 9121.020995 | 2.064261 | 4990514.00 | 6.190922 | 2.101666e+08 |
| 82 | Finland | 2018 | 209.5 | 49987.626158 | 8.049188 | 224090.00 | 7.858107 | 5.515525e+06 |
| 83 | Germany | 2018 | 161.6 | 47939.278288 | 8.537043 | 114190.00 | 7.118364 | 8.290578e+07 |
| 84 | Israel | 2018 | 129.9 | 42406.845426 | 6.914993 | 1400.00 | 6.927179 | 8.882800e+06 |
| 85 | Australia | 2018 | 228.8 | 57273.520475 | 15.865714 | 1340051.00 | 7.176993 | 2.496326e+07 |
| 86 | China | 2018 | 96.4 | 9905.406383 | 7.533193 | 2162190.40 | 5.131434 | 1.402760e+09 |
| 87 | India | 2018 | 24.5 | 1974.377731 | 1.795595 | 716272.00 | 3.818069 | 1.369003e+09 |
| 88 | New Zealand | 2018 | 191.1 | 43236.886692 | 6.613272 | 98551.50 | 7.370286 | 4.900600e+06 |
| 89 | South Africa | 2018 | 88.2 | 7067.724165 | 7.667377 | 171228.90 | 4.883922 | 5.733964e+07 |
| 90 | United States | 2019 | 288.4 | 65120.394663 | 14.673381 | 3097950.00 | 6.943701 | 3.283300e+08 |
| 91 | Brazil | 2019 | 58.9 | 8845.324149 | 2.050770 | 4977985.00 | 6.451149 | 2.117829e+08 |
| 92 | Finland | 2019 | 203.4 | 48629.858228 | 7.423040 | 224090.00 | 7.780348 | 5.521606e+06 |
| 93 | Germany | 2019 | 156.3 | 46805.138433 | 7.927188 | 114190.00 | 7.035472 | 8.309296e+07 |
| 94 | Israel | 2019 | 132.5 | 44452.232562 | 6.935752 | 1400.00 | 7.331780 | 9.054000e+06 |
| 95 | Australia | 2019 | 233.2 | 55049.571920 | 15.599045 | 1340051.00 | 7.233995 | 2.533483e+07 |
| 96 | China | 2019 | 99.1 | 10143.860221 | 7.645436 | 2180986.10 | 5.144120 | 1.407745e+09 |
| 97 | India | 2019 | 24.8 | 2050.163800 | 1.752534 | 718936.00 | 3.248770 | 1.383112e+09 |
| 98 | New Zealand | 2019 | 194.4 | 42796.430582 | 6.830053 | 98655.20 | 7.205174 | 4.979200e+06 |
| 99 | South Africa | 2019 | 88.9 | 6702.526617 | 7.688908 | 170864.90 | 5.034863 | 5.808706e+07 |
| 100 | United States | 2020 | 265.2 | 63528.634303 | 13.032828 | 3097950.00 | 7.028088 | 3.315115e+08 |
| 101 | Brazil | 2020 | 56.5 | 6923.699912 | 1.942523 | 4966196.00 | 6.109718 | 2.131963e+08 |
| 102 | Finland | 2020 | 197.9 | 49169.719339 | 6.570145 | 224090.00 | 7.889350 | 5.529543e+06 |
| 103 | Germany | 2020 | 144.6 | 46749.476228 | 7.255221 | 114190.00 | 7.311898 | 8.316087e+07 |
| 104 | Israel | 2020 | 121.0 | 44846.791595 | 6.345216 | 1400.00 | 7.194928 | 9.215100e+06 |
| 105 | Australia | 2020 | 218.4 | 51868.247557 | 14.776137 | 1340051.00 | 7.137368 | 2.564925e+07 |
| 106 | China | 2020 | 101.1 | 10408.719554 | 7.756138 | 2199781.80 | 5.771065 | 1.411100e+09 |
| 107 | India | 2020 | 23.2 | 1913.219733 | 1.576093 | 721600.00 | 4.225281 | 1.396387e+09 |
| 108 | New Zealand | 2020 | 174.3 | 41760.594784 | 6.160799 | 98925.90 | 7.257382 | 5.090200e+06 |
| 109 | South Africa | 2020 | 82.7 | 5753.066494 | 6.687563 | 170500.90 | 4.946801 | 5.880193e+07 |
merged_data['GDP_per_capita'] = merged_data['GDP_per_capita']/1000
merged_data['Forest_Area_per_capita'] = merged_data['ForestArea']*1000/merged_data['Population']
merged_data.drop(columns=['ForestArea'], inplace=True)
merged_data
| Country_name | year | Energy_consumption_per_capita | GDP_per_capita | CO2_per_capita | Life_ladder | Population | Forest_Area_per_capita | |
|---|---|---|---|---|---|---|---|---|
| 0 | United States | 2010 | 300.7 | 48.650643 | 17.431737 | 7.163616 | 3.093271e+08 | 9.980372 |
| 1 | Brazil | 2010 | 56.0 | 11.249292 | 2.026606 | 6.837331 | 1.963535e+08 | 26.054067 |
| 2 | Finland | 2010 | 242.8 | 46.505303 | 11.658082 | 7.393264 | 5.363352e+06 | 41.470334 |
| 3 | Germany | 2010 | 169.6 | 41.572456 | 9.453389 | 6.724531 | 8.177693e+07 | 1.395137 |
| 4 | Israel | 2010 | 135.0 | 31.266605 | 9.250262 | 7.358916 | 7.623600e+06 | 0.202004 |
| 5 | Australia | 2010 | 240.5 | 52.147024 | 17.973752 | 7.450047 | 2.203175e+07 | 58.799732 |
| 6 | China | 2010 | 76.2 | 4.550474 | 6.335420 | 4.652737 | 1.337705e+09 | 1.499661 |
| 7 | India | 2010 | 18.2 | 1.350634 | 1.338034 | 4.989277 | 1.240614e+09 | 0.560174 |
| 8 | New Zealand | 2010 | 188.9 | 33.676774 | 7.136622 | 7.223756 | 4.350700e+06 | 22.635714 |
| 9 | South Africa | 2010 | 102.7 | 8.059563 | 8.217612 | 4.652429 | 5.178492e+07 | 3.362772 |
| 10 | United States | 2011 | 295.4 | 50.065967 | 16.604190 | 7.115139 | 3.115835e+08 | 9.916925 |
| 11 | Brazil | 2011 | 58.0 | 13.200556 | 2.110628 | 7.037817 | 1.981853e+08 | 25.735588 |
| 12 | Finland | 2011 | 225.8 | 51.148932 | 10.230256 | 7.354225 | 5.388272e+06 | 41.340526 |
| 13 | Germany | 2011 | 163.3 | 46.705896 | 9.299003 | 6.621312 | 8.027498e+07 | 1.421489 |
| 14 | Israel | 2011 | 135.6 | 34.354716 | 8.991063 | 7.433148 | 7.765800e+06 | 0.201138 |
| 15 | Australia | 2011 | 243.3 | 62.609661 | 17.656055 | 7.405616 | 2.234002e+07 | 58.306016 |
| 16 | China | 2011 | 81.8 | 5.614386 | 6.901347 | 5.037208 | 1.345035e+09 | 1.505888 |
| 17 | India | 2011 | 19.0 | 1.449603 | 1.396878 | 4.634871 | 1.257621e+09 | 0.554717 |
| 18 | New Zealand | 2011 | 187.9 | 38.387627 | 6.909352 | 7.190638 | 4.384000e+06 | 22.463089 |
| 19 | South Africa | 2011 | 99.9 | 8.737041 | 7.808054 | 4.930511 | 5.244332e+07 | 3.313613 |
| 20 | United States | 2012 | 285.4 | 51.784419 | 15.789760 | 7.026227 | 3.138777e+08 | 9.853202 |
| 21 | Brazil | 2012 | 58.5 | 12.327513 | 2.271418 | 6.660004 | 1.999777e+08 | 25.427951 |
| 22 | Finland | 2012 | 218.5 | 47.708061 | 9.126037 | 7.420209 | 5.413971e+06 | 41.205984 |
| 23 | Germany | 2012 | 165.1 | 43.855854 | 9.451289 | 6.702362 | 8.042582e+07 | 1.419072 |
| 24 | Israel | 2012 | 139.3 | 33.156228 | 9.615473 | 7.110855 | 7.910500e+06 | 0.200240 |
| 25 | Australia | 2012 | 236.5 | 68.078044 | 17.405618 | 7.195586 | 2.273346e+07 | 57.609106 |
| 26 | China | 2012 | 84.6 | 6.300582 | 7.045200 | 5.094917 | 1.354190e+09 | 1.510009 |
| 27 | India | 2012 | 19.8 | 1.434018 | 1.498204 | 4.720147 | 1.274487e+09 | 0.549466 |
| 28 | New Zealand | 2012 | 187.1 | 39.973381 | 7.283728 | 7.249630 | 4.408100e+06 | 22.339593 |
| 29 | South Africa | 2012 | 96.9 | 8.173869 | 8.034649 | 5.133888 | 5.314503e+07 | 3.263012 |
| 30 | United States | 2013 | 290.9 | 53.291128 | 16.111175 | 7.249285 | 3.160599e+08 | 9.793870 |
| 31 | Brazil | 2013 | 60.2 | 12.258566 | 2.413447 | 7.140283 | 2.017218e+08 | 25.131802 |
| 32 | Finland | 2013 | 218.8 | 49.892223 | 9.228086 | 7.444636 | 5.438972e+06 | 41.077983 |
| 33 | Germany | 2013 | 169.3 | 46.298923 | 9.624229 | 6.965125 | 8.064560e+07 | 1.415452 |
| 34 | Israel | 2013 | 127.3 | 36.941842 | 8.313481 | 7.320563 | 8.059500e+06 | 0.199268 |
| 35 | Australia | 2013 | 235.9 | 68.198419 | 16.794588 | 7.364169 | 2.312813e+07 | 56.932898 |
| 36 | China | 2013 | 87.2 | 7.020386 | 7.320155 | 5.241090 | 1.363240e+09 | 1.514192 |
| 37 | India | 2013 | 20.3 | 1.438057 | 1.527674 | 4.427789 | 1.291132e+09 | 0.544446 |
| 38 | New Zealand | 2013 | 186.2 | 42.976650 | 7.178024 | 7.280152 | 4.442100e+06 | 22.167925 |
| 39 | South Africa | 2013 | 95.7 | 7.441231 | 8.116435 | 3.660727 | 5.387362e+07 | 3.212127 |
| 40 | United States | 2014 | 291.8 | 55.123850 | 16.040917 | 7.151114 | 3.183863e+08 | 9.730945 |
| 41 | Brazil | 2014 | 61.1 | 12.071404 | 2.514592 | 6.980999 | 2.034596e+08 | 24.841485 |
| 42 | Finland | 2014 | 210.1 | 50.327240 | 8.452183 | 7.384571 | 5.461512e+06 | 40.969607 |
| 43 | Germany | 2014 | 161.6 | 48.023870 | 9.088528 | 6.984214 | 8.098250e+07 | 1.409811 |
| 44 | Israel | 2014 | 123.2 | 38.259681 | 7.877332 | 7.400570 | 8.215700e+06 | 0.198157 |
| 45 | Australia | 2014 | 234.8 | 62.558244 | 16.155745 | 7.288550 | 2.347569e+07 | 56.392312 |
| 46 | China | 2014 | 89.2 | 7.636074 | 7.304713 | 5.195619 | 1.371860e+09 | 1.518795 |
| 47 | India | 2014 | 21.4 | 1.559864 | 1.642465 | 4.424379 | 1.307247e+09 | 0.539773 |
| 48 | New Zealand | 2014 | 192.6 | 44.572899 | 7.078645 | 7.305892 | 4.516500e+06 | 21.802086 |
| 49 | South Africa | 2014 | 95.3 | 6.965138 | 8.191153 | 4.828456 | 5.472955e+07 | 3.155241 |
| 50 | United States | 2015 | 287.0 | 56.762729 | 15.560015 | 6.863947 | 3.207390e+08 | 9.668142 |
| 51 | Brazil | 2015 | 59.7 | 8.783215 | 2.365361 | 6.546897 | 2.051882e+08 | 24.557201 |
| 52 | Finland | 2015 | 207.9 | 42.801908 | 7.813698 | 7.447926 | 5.479531e+06 | 40.895836 |
| 53 | Germany | 2015 | 163.8 | 41.103256 | 9.087345 | 7.037138 | 8.168661e+07 | 1.397904 |
| 54 | Israel | 2015 | 128.0 | 36.206522 | 7.913354 | 7.079411 | 8.380100e+06 | 0.196895 |
| 55 | Australia | 2015 | 237.0 | 56.758869 | 16.198458 | 7.309061 | 2.381600e+07 | 55.884501 |
| 56 | China | 2015 | 89.9 | 8.016446 | 7.145132 | 5.303878 | 1.379860e+09 | 1.524026 |
| 57 | India | 2015 | 21.9 | 1.590174 | 1.631323 | 4.342079 | 1.322867e+09 | 0.535413 |
| 58 | New Zealand | 2015 | 192.3 | 38.630727 | 7.003341 | 7.418121 | 4.609400e+06 | 21.362021 |
| 59 | South Africa | 2015 | 91.9 | 6.204930 | 7.607189 | 4.887326 | 5.587650e+07 | 3.083960 |
| 60 | United States | 2016 | 284.7 | 57.866745 | 15.149883 | 6.803600 | 3.230718e+08 | 9.598332 |
| 61 | Brazil | 2016 | 57.7 | 8.680736 | 2.161260 | 6.374817 | 2.068596e+08 | 24.271639 |
| 62 | Finland | 2016 | 210.9 | 43.814027 | 8.316248 | 7.659843 | 5.495303e+06 | 40.778461 |
| 63 | Germany | 2016 | 165.7 | 42.136121 | 9.072972 | 6.873763 | 8.234867e+07 | 1.386665 |
| 64 | Israel | 2016 | 128.1 | 37.690474 | 7.633162 | 7.159011 | 8.546000e+06 | 0.163819 |
| 65 | Australia | 2016 | 234.8 | 49.918794 | 16.320331 | 7.250080 | 2.419091e+07 | 55.408092 |
| 66 | China | 2016 | 91.0 | 8.094390 | 7.105480 | 5.324956 | 1.387790e+09 | 1.530922 |
| 67 | India | 2016 | 22.6 | 1.714280 | 1.639914 | 4.179177 | 1.338636e+09 | 0.531096 |
| 68 | New Zealand | 2016 | 191.7 | 40.058196 | 6.615409 | 7.225688 | 4.714100e+06 | 20.887868 |
| 69 | South Africa | 2016 | 94.8 | 5.735067 | 7.544590 | 4.769740 | 5.642227e+07 | 3.047678 |
| 70 | United States | 2017 | 283.8 | 59.907754 | 14.823245 | 6.991759 | 3.251221e+08 | 9.528573 |
| 71 | Brazil | 2017 | 57.9 | 9.896719 | 2.185487 | 6.332929 | 2.085050e+08 | 23.984638 |
| 72 | Finland | 2017 | 205.7 | 46.412136 | 7.809319 | 7.788252 | 5.508214e+06 | 40.682878 |
| 73 | Germany | 2017 | 166.7 | 44.652589 | 8.858345 | 7.074325 | 8.265700e+07 | 1.381492 |
| 74 | Israel | 2017 | 131.7 | 41.114782 | 7.563874 | 7.331036 | 8.713300e+06 | 0.160674 |
| 75 | Australia | 2017 | 230.5 | 53.954553 | 16.149150 | 7.257038 | 2.459259e+07 | 54.495037 |
| 76 | China | 2017 | 93.5 | 8.817046 | 7.226160 | 5.099061 | 1.396215e+09 | 1.535147 |
| 77 | India | 2017 | 23.3 | 1.957970 | 1.704927 | 4.046111 | 1.354196e+09 | 0.526961 |
| 78 | New Zealand | 2017 | 193.2 | 42.910973 | 6.840494 | 7.327183 | 4.813600e+06 | 20.464621 |
| 79 | South Africa | 2017 | 92.9 | 6.734475 | 7.683708 | 4.513655 | 5.664121e+07 | 3.029471 |
| 80 | United States | 2018 | 292.4 | 62.823309 | 15.222518 | 6.882685 | 3.268382e+08 | 9.478543 |
| 81 | Brazil | 2018 | 57.8 | 9.121021 | 2.064261 | 6.190922 | 2.101666e+08 | 23.745515 |
| 82 | Finland | 2018 | 209.5 | 49.987626 | 8.049188 | 7.858107 | 5.515525e+06 | 40.628952 |
| 83 | Germany | 2018 | 161.6 | 47.939278 | 8.537043 | 7.118364 | 8.290578e+07 | 1.377347 |
| 84 | Israel | 2018 | 129.9 | 42.406845 | 6.914993 | 6.927179 | 8.882800e+06 | 0.157608 |
| 85 | Australia | 2018 | 228.8 | 57.273520 | 15.865714 | 7.176993 | 2.496326e+07 | 53.680934 |
| 86 | China | 2018 | 96.4 | 9.905406 | 7.533193 | 5.131434 | 1.402760e+09 | 1.541383 |
| 87 | India | 2018 | 24.5 | 1.974378 | 1.795595 | 3.818069 | 1.369003e+09 | 0.523207 |
| 88 | New Zealand | 2018 | 191.1 | 43.236887 | 6.613272 | 7.370286 | 4.900600e+06 | 20.110089 |
| 89 | South Africa | 2018 | 88.2 | 7.067724 | 7.667377 | 4.883922 | 5.733964e+07 | 2.986222 |
| 90 | United States | 2019 | 288.4 | 65.120395 | 14.673381 | 6.943701 | 3.283300e+08 | 9.435478 |
| 91 | Brazil | 2019 | 58.9 | 8.845324 | 2.050770 | 6.451149 | 2.117829e+08 | 23.505134 |
| 92 | Finland | 2019 | 203.4 | 48.629858 | 7.423040 | 7.780348 | 5.521606e+06 | 40.584207 |
| 93 | Germany | 2019 | 156.3 | 46.805138 | 7.927188 | 7.035472 | 8.309296e+07 | 1.374244 |
| 94 | Israel | 2019 | 132.5 | 44.452233 | 6.935752 | 7.331780 | 9.054000e+06 | 0.154628 |
| 95 | Australia | 2019 | 233.2 | 55.049572 | 15.599045 | 7.233995 | 2.533483e+07 | 52.893633 |
| 96 | China | 2019 | 99.1 | 10.143860 | 7.645436 | 5.144120 | 1.407745e+09 | 1.549276 |
| 97 | India | 2019 | 24.8 | 2.050164 | 1.752534 | 3.248770 | 1.383112e+09 | 0.519796 |
| 98 | New Zealand | 2019 | 194.4 | 42.796431 | 6.830053 | 7.205174 | 4.979200e+06 | 19.813464 |
| 99 | South Africa | 2019 | 88.9 | 6.702527 | 7.688908 | 5.034863 | 5.808706e+07 | 2.941531 |
| 100 | United States | 2020 | 265.2 | 63.528634 | 13.032828 | 7.028088 | 3.315115e+08 | 9.344924 |
| 101 | Brazil | 2020 | 56.5 | 6.923700 | 1.942523 | 6.109718 | 2.131963e+08 | 23.294006 |
| 102 | Finland | 2020 | 197.9 | 49.169719 | 6.570145 | 7.889350 | 5.529543e+06 | 40.525953 |
| 103 | Germany | 2020 | 144.6 | 46.749476 | 7.255221 | 7.311898 | 8.316087e+07 | 1.373122 |
| 104 | Israel | 2020 | 121.0 | 44.846792 | 6.345216 | 7.194928 | 9.215100e+06 | 0.151925 |
| 105 | Australia | 2020 | 218.4 | 51.868248 | 14.776137 | 7.137368 | 2.564925e+07 | 52.245235 |
| 106 | China | 2020 | 101.1 | 10.408720 | 7.756138 | 5.771065 | 1.411100e+09 | 1.558913 |
| 107 | India | 2020 | 23.2 | 1.913220 | 1.576093 | 4.225281 | 1.396387e+09 | 0.516762 |
| 108 | New Zealand | 2020 | 174.3 | 41.760595 | 6.160799 | 7.257382 | 5.090200e+06 | 19.434580 |
| 109 | South Africa | 2020 | 82.7 | 5.753066 | 6.687563 | 4.946801 | 5.880193e+07 | 2.899580 |
Adjust the unit of GDP per capita and calculate the Forest area per capita for data analysis in next steps.
from IPython.core.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
C:\Users\lpxue\AppData\Local\Temp\ipykernel_19860\3777615979.py:1: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display from IPython.core.display import display, HTML
import pandas as pd
import sqlite3
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from pylab import rcParams
rcParams['figure.figsize'] = 15, 10
rcParams['font.size'] = 20
rcParams['axes.facecolor'] = 'white'
%matplotlib inline
connection = sqlite3.connect('./datasets/mySQLiteDB.sl3')
cursor = connection.cursor()
%load_ext sql
The sql extension is already loaded. To reload it, use: %reload_ext sql
merged_data.head(1)
| Country_name | year | Energy_consumption_per_capita | GDP_per_capita | CO2_per_capita | Life_ladder | Population | Forest_Area_per_capita | |
|---|---|---|---|---|---|---|---|---|
| 0 | United States | 2010 | 300.7 | 48.650643 | 17.431737 | 7.163616 | 309327143.0 | 9.980372 |
print (merged_data.info())
<class 'pandas.core.frame.DataFrame'> RangeIndex: 110 entries, 0 to 109 Data columns (total 8 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 Country_name 110 non-null object 1 year 110 non-null int32 2 Energy_consumption_per_capita 110 non-null float64 3 GDP_per_capita 110 non-null float64 4 CO2_per_capita 110 non-null float64 5 Life_ladder 110 non-null float64 6 Population 110 non-null float64 7 Forest_Area_per_capita 110 non-null float64 dtypes: float64(6), int32(1), object(1) memory usage: 6.6+ KB None
cursor.execute('DROP TABLE IF EXISTS merged_data')
table = """
CREATE TABLE merged_data (
Country_name VARCHAR(20) NOT NULL,
year INTEGER NOT NULL,
Energy_consumption_per_capita NUMBER NOT NULL,
GDP_per_capita NUMBER NOT NULL,
CO2_per_capita NUMBER NOT NULL,
Life_ladder NUMBER NOT NULL,
Population NUMBER NOT NULL,
Forest_Area_per_capita NUMBER NOT NULL);
"""
cursor.execute(table)
<sqlite3.Cursor at 0x1a9b98e0440>
add_row_merged_data = """
INSERT INTO merged_data
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
"""
merged_data
| Country_name | year | Energy_consumption_per_capita | GDP_per_capita | CO2_per_capita | Life_ladder | Population | Forest_Area_per_capita | |
|---|---|---|---|---|---|---|---|---|
| 0 | United States | 2010 | 300.7 | 48.650643 | 17.431737 | 7.163616 | 3.093271e+08 | 9.980372 |
| 1 | Brazil | 2010 | 56.0 | 11.249292 | 2.026606 | 6.837331 | 1.963535e+08 | 26.054067 |
| 2 | Finland | 2010 | 242.8 | 46.505303 | 11.658082 | 7.393264 | 5.363352e+06 | 41.470334 |
| 3 | Germany | 2010 | 169.6 | 41.572456 | 9.453389 | 6.724531 | 8.177693e+07 | 1.395137 |
| 4 | Israel | 2010 | 135.0 | 31.266605 | 9.250262 | 7.358916 | 7.623600e+06 | 0.202004 |
| 5 | Australia | 2010 | 240.5 | 52.147024 | 17.973752 | 7.450047 | 2.203175e+07 | 58.799732 |
| 6 | China | 2010 | 76.2 | 4.550474 | 6.335420 | 4.652737 | 1.337705e+09 | 1.499661 |
| 7 | India | 2010 | 18.2 | 1.350634 | 1.338034 | 4.989277 | 1.240614e+09 | 0.560174 |
| 8 | New Zealand | 2010 | 188.9 | 33.676774 | 7.136622 | 7.223756 | 4.350700e+06 | 22.635714 |
| 9 | South Africa | 2010 | 102.7 | 8.059563 | 8.217612 | 4.652429 | 5.178492e+07 | 3.362772 |
| 10 | United States | 2011 | 295.4 | 50.065967 | 16.604190 | 7.115139 | 3.115835e+08 | 9.916925 |
| 11 | Brazil | 2011 | 58.0 | 13.200556 | 2.110628 | 7.037817 | 1.981853e+08 | 25.735588 |
| 12 | Finland | 2011 | 225.8 | 51.148932 | 10.230256 | 7.354225 | 5.388272e+06 | 41.340526 |
| 13 | Germany | 2011 | 163.3 | 46.705896 | 9.299003 | 6.621312 | 8.027498e+07 | 1.421489 |
| 14 | Israel | 2011 | 135.6 | 34.354716 | 8.991063 | 7.433148 | 7.765800e+06 | 0.201138 |
| 15 | Australia | 2011 | 243.3 | 62.609661 | 17.656055 | 7.405616 | 2.234002e+07 | 58.306016 |
| 16 | China | 2011 | 81.8 | 5.614386 | 6.901347 | 5.037208 | 1.345035e+09 | 1.505888 |
| 17 | India | 2011 | 19.0 | 1.449603 | 1.396878 | 4.634871 | 1.257621e+09 | 0.554717 |
| 18 | New Zealand | 2011 | 187.9 | 38.387627 | 6.909352 | 7.190638 | 4.384000e+06 | 22.463089 |
| 19 | South Africa | 2011 | 99.9 | 8.737041 | 7.808054 | 4.930511 | 5.244332e+07 | 3.313613 |
| 20 | United States | 2012 | 285.4 | 51.784419 | 15.789760 | 7.026227 | 3.138777e+08 | 9.853202 |
| 21 | Brazil | 2012 | 58.5 | 12.327513 | 2.271418 | 6.660004 | 1.999777e+08 | 25.427951 |
| 22 | Finland | 2012 | 218.5 | 47.708061 | 9.126037 | 7.420209 | 5.413971e+06 | 41.205984 |
| 23 | Germany | 2012 | 165.1 | 43.855854 | 9.451289 | 6.702362 | 8.042582e+07 | 1.419072 |
| 24 | Israel | 2012 | 139.3 | 33.156228 | 9.615473 | 7.110855 | 7.910500e+06 | 0.200240 |
| 25 | Australia | 2012 | 236.5 | 68.078044 | 17.405618 | 7.195586 | 2.273346e+07 | 57.609106 |
| 26 | China | 2012 | 84.6 | 6.300582 | 7.045200 | 5.094917 | 1.354190e+09 | 1.510009 |
| 27 | India | 2012 | 19.8 | 1.434018 | 1.498204 | 4.720147 | 1.274487e+09 | 0.549466 |
| 28 | New Zealand | 2012 | 187.1 | 39.973381 | 7.283728 | 7.249630 | 4.408100e+06 | 22.339593 |
| 29 | South Africa | 2012 | 96.9 | 8.173869 | 8.034649 | 5.133888 | 5.314503e+07 | 3.263012 |
| 30 | United States | 2013 | 290.9 | 53.291128 | 16.111175 | 7.249285 | 3.160599e+08 | 9.793870 |
| 31 | Brazil | 2013 | 60.2 | 12.258566 | 2.413447 | 7.140283 | 2.017218e+08 | 25.131802 |
| 32 | Finland | 2013 | 218.8 | 49.892223 | 9.228086 | 7.444636 | 5.438972e+06 | 41.077983 |
| 33 | Germany | 2013 | 169.3 | 46.298923 | 9.624229 | 6.965125 | 8.064560e+07 | 1.415452 |
| 34 | Israel | 2013 | 127.3 | 36.941842 | 8.313481 | 7.320563 | 8.059500e+06 | 0.199268 |
| 35 | Australia | 2013 | 235.9 | 68.198419 | 16.794588 | 7.364169 | 2.312813e+07 | 56.932898 |
| 36 | China | 2013 | 87.2 | 7.020386 | 7.320155 | 5.241090 | 1.363240e+09 | 1.514192 |
| 37 | India | 2013 | 20.3 | 1.438057 | 1.527674 | 4.427789 | 1.291132e+09 | 0.544446 |
| 38 | New Zealand | 2013 | 186.2 | 42.976650 | 7.178024 | 7.280152 | 4.442100e+06 | 22.167925 |
| 39 | South Africa | 2013 | 95.7 | 7.441231 | 8.116435 | 3.660727 | 5.387362e+07 | 3.212127 |
| 40 | United States | 2014 | 291.8 | 55.123850 | 16.040917 | 7.151114 | 3.183863e+08 | 9.730945 |
| 41 | Brazil | 2014 | 61.1 | 12.071404 | 2.514592 | 6.980999 | 2.034596e+08 | 24.841485 |
| 42 | Finland | 2014 | 210.1 | 50.327240 | 8.452183 | 7.384571 | 5.461512e+06 | 40.969607 |
| 43 | Germany | 2014 | 161.6 | 48.023870 | 9.088528 | 6.984214 | 8.098250e+07 | 1.409811 |
| 44 | Israel | 2014 | 123.2 | 38.259681 | 7.877332 | 7.400570 | 8.215700e+06 | 0.198157 |
| 45 | Australia | 2014 | 234.8 | 62.558244 | 16.155745 | 7.288550 | 2.347569e+07 | 56.392312 |
| 46 | China | 2014 | 89.2 | 7.636074 | 7.304713 | 5.195619 | 1.371860e+09 | 1.518795 |
| 47 | India | 2014 | 21.4 | 1.559864 | 1.642465 | 4.424379 | 1.307247e+09 | 0.539773 |
| 48 | New Zealand | 2014 | 192.6 | 44.572899 | 7.078645 | 7.305892 | 4.516500e+06 | 21.802086 |
| 49 | South Africa | 2014 | 95.3 | 6.965138 | 8.191153 | 4.828456 | 5.472955e+07 | 3.155241 |
| 50 | United States | 2015 | 287.0 | 56.762729 | 15.560015 | 6.863947 | 3.207390e+08 | 9.668142 |
| 51 | Brazil | 2015 | 59.7 | 8.783215 | 2.365361 | 6.546897 | 2.051882e+08 | 24.557201 |
| 52 | Finland | 2015 | 207.9 | 42.801908 | 7.813698 | 7.447926 | 5.479531e+06 | 40.895836 |
| 53 | Germany | 2015 | 163.8 | 41.103256 | 9.087345 | 7.037138 | 8.168661e+07 | 1.397904 |
| 54 | Israel | 2015 | 128.0 | 36.206522 | 7.913354 | 7.079411 | 8.380100e+06 | 0.196895 |
| 55 | Australia | 2015 | 237.0 | 56.758869 | 16.198458 | 7.309061 | 2.381600e+07 | 55.884501 |
| 56 | China | 2015 | 89.9 | 8.016446 | 7.145132 | 5.303878 | 1.379860e+09 | 1.524026 |
| 57 | India | 2015 | 21.9 | 1.590174 | 1.631323 | 4.342079 | 1.322867e+09 | 0.535413 |
| 58 | New Zealand | 2015 | 192.3 | 38.630727 | 7.003341 | 7.418121 | 4.609400e+06 | 21.362021 |
| 59 | South Africa | 2015 | 91.9 | 6.204930 | 7.607189 | 4.887326 | 5.587650e+07 | 3.083960 |
| 60 | United States | 2016 | 284.7 | 57.866745 | 15.149883 | 6.803600 | 3.230718e+08 | 9.598332 |
| 61 | Brazil | 2016 | 57.7 | 8.680736 | 2.161260 | 6.374817 | 2.068596e+08 | 24.271639 |
| 62 | Finland | 2016 | 210.9 | 43.814027 | 8.316248 | 7.659843 | 5.495303e+06 | 40.778461 |
| 63 | Germany | 2016 | 165.7 | 42.136121 | 9.072972 | 6.873763 | 8.234867e+07 | 1.386665 |
| 64 | Israel | 2016 | 128.1 | 37.690474 | 7.633162 | 7.159011 | 8.546000e+06 | 0.163819 |
| 65 | Australia | 2016 | 234.8 | 49.918794 | 16.320331 | 7.250080 | 2.419091e+07 | 55.408092 |
| 66 | China | 2016 | 91.0 | 8.094390 | 7.105480 | 5.324956 | 1.387790e+09 | 1.530922 |
| 67 | India | 2016 | 22.6 | 1.714280 | 1.639914 | 4.179177 | 1.338636e+09 | 0.531096 |
| 68 | New Zealand | 2016 | 191.7 | 40.058196 | 6.615409 | 7.225688 | 4.714100e+06 | 20.887868 |
| 69 | South Africa | 2016 | 94.8 | 5.735067 | 7.544590 | 4.769740 | 5.642227e+07 | 3.047678 |
| 70 | United States | 2017 | 283.8 | 59.907754 | 14.823245 | 6.991759 | 3.251221e+08 | 9.528573 |
| 71 | Brazil | 2017 | 57.9 | 9.896719 | 2.185487 | 6.332929 | 2.085050e+08 | 23.984638 |
| 72 | Finland | 2017 | 205.7 | 46.412136 | 7.809319 | 7.788252 | 5.508214e+06 | 40.682878 |
| 73 | Germany | 2017 | 166.7 | 44.652589 | 8.858345 | 7.074325 | 8.265700e+07 | 1.381492 |
| 74 | Israel | 2017 | 131.7 | 41.114782 | 7.563874 | 7.331036 | 8.713300e+06 | 0.160674 |
| 75 | Australia | 2017 | 230.5 | 53.954553 | 16.149150 | 7.257038 | 2.459259e+07 | 54.495037 |
| 76 | China | 2017 | 93.5 | 8.817046 | 7.226160 | 5.099061 | 1.396215e+09 | 1.535147 |
| 77 | India | 2017 | 23.3 | 1.957970 | 1.704927 | 4.046111 | 1.354196e+09 | 0.526961 |
| 78 | New Zealand | 2017 | 193.2 | 42.910973 | 6.840494 | 7.327183 | 4.813600e+06 | 20.464621 |
| 79 | South Africa | 2017 | 92.9 | 6.734475 | 7.683708 | 4.513655 | 5.664121e+07 | 3.029471 |
| 80 | United States | 2018 | 292.4 | 62.823309 | 15.222518 | 6.882685 | 3.268382e+08 | 9.478543 |
| 81 | Brazil | 2018 | 57.8 | 9.121021 | 2.064261 | 6.190922 | 2.101666e+08 | 23.745515 |
| 82 | Finland | 2018 | 209.5 | 49.987626 | 8.049188 | 7.858107 | 5.515525e+06 | 40.628952 |
| 83 | Germany | 2018 | 161.6 | 47.939278 | 8.537043 | 7.118364 | 8.290578e+07 | 1.377347 |
| 84 | Israel | 2018 | 129.9 | 42.406845 | 6.914993 | 6.927179 | 8.882800e+06 | 0.157608 |
| 85 | Australia | 2018 | 228.8 | 57.273520 | 15.865714 | 7.176993 | 2.496326e+07 | 53.680934 |
| 86 | China | 2018 | 96.4 | 9.905406 | 7.533193 | 5.131434 | 1.402760e+09 | 1.541383 |
| 87 | India | 2018 | 24.5 | 1.974378 | 1.795595 | 3.818069 | 1.369003e+09 | 0.523207 |
| 88 | New Zealand | 2018 | 191.1 | 43.236887 | 6.613272 | 7.370286 | 4.900600e+06 | 20.110089 |
| 89 | South Africa | 2018 | 88.2 | 7.067724 | 7.667377 | 4.883922 | 5.733964e+07 | 2.986222 |
| 90 | United States | 2019 | 288.4 | 65.120395 | 14.673381 | 6.943701 | 3.283300e+08 | 9.435478 |
| 91 | Brazil | 2019 | 58.9 | 8.845324 | 2.050770 | 6.451149 | 2.117829e+08 | 23.505134 |
| 92 | Finland | 2019 | 203.4 | 48.629858 | 7.423040 | 7.780348 | 5.521606e+06 | 40.584207 |
| 93 | Germany | 2019 | 156.3 | 46.805138 | 7.927188 | 7.035472 | 8.309296e+07 | 1.374244 |
| 94 | Israel | 2019 | 132.5 | 44.452233 | 6.935752 | 7.331780 | 9.054000e+06 | 0.154628 |
| 95 | Australia | 2019 | 233.2 | 55.049572 | 15.599045 | 7.233995 | 2.533483e+07 | 52.893633 |
| 96 | China | 2019 | 99.1 | 10.143860 | 7.645436 | 5.144120 | 1.407745e+09 | 1.549276 |
| 97 | India | 2019 | 24.8 | 2.050164 | 1.752534 | 3.248770 | 1.383112e+09 | 0.519796 |
| 98 | New Zealand | 2019 | 194.4 | 42.796431 | 6.830053 | 7.205174 | 4.979200e+06 | 19.813464 |
| 99 | South Africa | 2019 | 88.9 | 6.702527 | 7.688908 | 5.034863 | 5.808706e+07 | 2.941531 |
| 100 | United States | 2020 | 265.2 | 63.528634 | 13.032828 | 7.028088 | 3.315115e+08 | 9.344924 |
| 101 | Brazil | 2020 | 56.5 | 6.923700 | 1.942523 | 6.109718 | 2.131963e+08 | 23.294006 |
| 102 | Finland | 2020 | 197.9 | 49.169719 | 6.570145 | 7.889350 | 5.529543e+06 | 40.525953 |
| 103 | Germany | 2020 | 144.6 | 46.749476 | 7.255221 | 7.311898 | 8.316087e+07 | 1.373122 |
| 104 | Israel | 2020 | 121.0 | 44.846792 | 6.345216 | 7.194928 | 9.215100e+06 | 0.151925 |
| 105 | Australia | 2020 | 218.4 | 51.868248 | 14.776137 | 7.137368 | 2.564925e+07 | 52.245235 |
| 106 | China | 2020 | 101.1 | 10.408720 | 7.756138 | 5.771065 | 1.411100e+09 | 1.558913 |
| 107 | India | 2020 | 23.2 | 1.913220 | 1.576093 | 4.225281 | 1.396387e+09 | 0.516762 |
| 108 | New Zealand | 2020 | 174.3 | 41.760595 | 6.160799 | 7.257382 | 5.090200e+06 | 19.434580 |
| 109 | South Africa | 2020 | 82.7 | 5.753066 | 6.687563 | 4.946801 | 5.880193e+07 | 2.899580 |
for index, row in merged_data.iterrows():
substitution_values = (row['Country_name'], row['year'], row['Energy_consumption_per_capita'],\
row['GDP_per_capita'], row['CO2_per_capita'], row['Life_ladder'], \
row['Population'], row['Forest_Area_per_capita'])
cursor.execute(add_row_merged_data, substitution_values)
connection.commit()
#Check
sql_statement = 'SELECT * FROM merged_data;'
cursor.execute(sql_statement)
for (Country_nam, year, Energy_consumption_per_capita, GDP_per_capita, CO2_per_capita, Life_ladder, Population, Forest_Area_per_capita) in cursor:
print(Country_nam, year, Energy_consumption_per_capita, GDP_per_capita, CO2_per_capita, Life_ladder, Population, Forest_Area_per_capita)
United States 2010 300.7 48.6506431283336 17.4317369879177 7.163616180419922 309327143 9.98037213953772 Brazil 2010 56 11.249291890435199 2.02660566892286 6.837331295013428 196353492 26.05406681537398 Finland 2010 242.8 46.5053031791811 11.6580824827459 7.393264293670654 5363352 41.47033422382122 Germany 2010 169.6 41.572455948150704 9.45338862684134 6.724531173706055 81776930 1.3951367457790358 Israel 2010 135 31.2666053174383 9.25026234324991 7.358916282653809 7623600 0.20200430242929848 Australia 2010 240.5 52.1470241942843 17.9737515176961 7.450047016143799 22031750 58.799732204659186 China 2010 76.2 4.550473943611309 6.33541976743751 4.652736663818359 1337705000 1.499660837030586 India 2010 18.2 1.35063447029491 1.33803383522422 4.989277362823486 1240613620 0.5601744078869616 New Zealand 2010 188.9 33.6767741239925 7.13662169306089 7.223756313323975 4350700 22.635713793182706 South Africa 2010 102.7 8.05956279824609 8.21761222731227 4.65242862701416 51784921 3.3627723406201584 United States 2011 295.4 50.0659665041742 16.604189616843 7.115138530731201 311583481 9.916924960473112 Brazil 2011 58 13.200556234878901 2.11062775987293 7.037816524505615 198185302 25.735587596702807 Finland 2011 225.8 51.1489316365833 10.2302556366865 7.354225158691406 5388272 41.3405262392099 Germany 2011 163.3 46.705895796335305 9.29900290355714 6.621312141418457 80274983 1.4214889338562675 Israel 2011 135.6 34.3547161182231 8.99106338046306 7.43314790725708 7765800 0.2011383244482217 Australia 2011 243.3 62.6096607161044 17.6560553381679 7.405616283416748 22340024 58.30601614393969 China 2011 81.8 5.6143860223103 6.90134732553428 5.03720760345459 1345035000 1.5058876088726316 India 2011 19 1.44960330101563 1.39687849773199 4.634871482849121 1257621191 0.5547171159268419 New Zealand 2011 187.9 38.3876270784076 6.90935218978102 7.190638065338135 4384000 22.463088503649637 South Africa 2011 99.9 8.737041269424349 7.8080537418251 4.930511474609375 52443325 3.313613314945229 United States 2012 285.4 51.7844185738837 15.789760151839 7.026226997375488 313877662 9.853201977782032 Brazil 2012 58.5 12.3275131013057 2.2714176835721 6.660003662109375 199977707 25.42795132659462 Finland 2012 218.5 47.7080612784469 9.12603706225985 7.4202094078063965 5413971 41.20598355624735 Germany 2012 165.1 43.855854465861796 9.45128904680279 6.702362060546875 80425823 1.4190715835136682 Israel 2012 139.3 33.1562283157638 9.61547310536628 7.110854625701904 7910500 0.2002401870931041 Australia 2012 236.5 68.0780442283168 17.4056176654109 7.19558572769165 22733465 57.609106222918506 China 2012 84.6 6.30058217952904 7.04520023039603 5.094917297363281 1354190000 1.5100091419963226 India 2012 19.8 1.4340179872162901 1.49820412282441 4.720146656036377 1274487215 0.5494664769940435 New Zealand 2012 187.1 39.9733807587223 7.28372768312879 7.249629974365234 4408100 22.33959302193689 South Africa 2012 96.9 8.1738691381716 8.03464925875575 5.133887767791748 53145033 3.2630123684371406 United States 2013 290.9 53.2911276891406 16.1111752638496 7.2492852210998535 316059947 9.79386989519428 Brazil 2013 60.2 12.2585657091866 2.4134465369818 7.14028263092041 201721767 25.13180245937465 Finland 2013 218.8 49.8922233632732 9.2280857485569 7.44463586807251 5438972 41.07798311886879 Germany 2013 169.3 46.298922917734096 9.62422936749002 6.96512508392334 80645605 1.4154522121819286 Israel 2013 127.3 36.9418423573582 8.31348098517278 7.320563316345215 8059500 0.19926794466157952 Australia 2013 235.9 68.1984193446869 16.7945880965987 7.364169120788574 23128129 56.932897598417924 China 2013 87.2 7.020386074240649 7.32015492503154 5.241090297698975 1363240000 1.514191939790499 India 2013 20.3 1.43805700508042 1.52767440026001 4.427788734436035 1291132063 0.5444462422896239 New Zealand 2013 186.2 42.9766495882584 7.17802390761126 7.280151844024658 4442100 22.167925080479954 South Africa 2013 95.7 7.44123085399675 8.11643495398564 3.6607272624969482 53873616 3.2121270642015194 United States 2014 291.8 55.1238497869046 16.0409167568247 7.151114463806152 318386329 9.730945451492675 Brazil 2014 61.1 12.0714044637296 2.51459195963426 6.980998992919922 203459650 24.841484785803967 Finland 2014 210.1 50.327240290263205 8.45218320494398 7.384571075439453 5461512 40.96960695133509 Germany 2014 161.6 48.0238699845462 9.08852776834501 6.9842143058776855 80982500 1.409810761584293 Israel 2014 123.2 38.259681095617296 7.8773324245043 7.400570392608643 8215700 0.1981571868495685 Australia 2014 234.8 62.5582438786332 16.1557451398864 7.28855037689209 23475686 56.39231160273655 China 2014 89.2 7.636074340158699 7.30471287157582 5.195619106292725 1371860000 1.5187954747568995 India 2014 21.4 1.55986377870535 1.64246527737333 4.424379348754883 1307246509 0.5397727170369517 New Zealand 2014 192.6 44.5728987536626 7.07864496844902 7.305892467498779 4516500 21.802085685818664 South Africa 2014 95.3 6.9651378973693 8.19115252745267 4.828456401824951 54729551 3.155240575607865 United States 2015 287 56.7627294515989 15.5600154435853 6.863946914672852 320738994 9.668141566846717 Brazil 2015 59.7 8.7832154236384 2.36536062099671 6.546896934509277 205188205 24.557201034045793 Finland 2015 207.9 42.8019081167285 7.81369792414716 7.447925567626953 5479531 40.89583579324581 Germany 2015 163.8 41.1032564363768 9.08734480366678 7.037137508392334 81686611 1.3979035070998356 Israel 2015 128 36.206522217162096 7.9133542559158 7.079411029815674 8380100 0.19689502511903198 Australia 2015 237 56.7588692027821 16.1984582210401 7.309060573577881 23815995 55.884501151432055 China 2015 89.9 8.01644559491162 7.14513153508327 5.303877830505371 1379860000 1.5240259881437248 India 2015 21.9 1.59017433135955 1.63132348717228 4.342079162597656 1322866505 0.5354130574195769 New Zealand 2015 192.3 38.6307265886928 7.00334099882848 7.418120861053467 4609400 21.362021087343255 South Africa 2015 91.9 6.204929901458461 7.60718852417825 4.887325763702393 55876504 3.083959941373569 United States 2016 284.7 57.8667449341091 15.1498827249693 6.803599834442139 323071755 9.59833211046258 Brazil 2016 57.7 8.68073646873878 2.16125984748939 6.374817371368408 206859578 24.271638995608896 Finland 2016 210.9 43.8140265056965 8.31624752993602 7.659843444824219 5495303 40.778461169475094 Germany 2016 165.7 42.1361207907991 9.07297238768971 6.873763084411621 82348669 1.3866647923599105 Israel 2016 128.1 37.6904739511859 7.63316171308214 7.159010887145996 8546000 0.16381933068102036 Australia 2016 234.8 49.9187939327254 16.3203306101751 7.250080108642578 24190907 55.40809197439352 China 2016 91 8.09439016730811 7.10547993572515 5.324955940246582 1387790000 1.5309223081301926 India 2016 22.6 1.7142795374003899 1.63991401876928 4.179177284240723 1338636340 0.5310956969836931 New Zealand 2016 191.7 40.0581961621466 6.61540909187332 7.2256879806518555 4714100 20.887868309963725 South Africa 2016 94.8 5.73506678717842 7.54458957113285 4.769739627838135 56422274 3.0476775891733823 United States 2017 283.8 59.907754260885 14.8232454359428 6.991759300231934 325122128 9.528573213570994 Brazil 2017 57.9 9.89671889500528 2.18548661863967 6.3329291343688965 208504960 23.98463806328636 Finland 2017 205.7 46.4121364777169 7.80931895529113 7.788251876831055 5508214 40.68287833406618 Germany 2017 166.7 44.6525891722719 8.8583445114547 7.074324607849121 82657002 1.381492157191958 Israel 2017 131.7 41.1147817082553 7.56387361849127 7.33103609085083 8713300 0.1606739122949973 Australia 2017 230.5 53.954553494614004 16.1491503049618 7.25703763961792 24592588 54.495037285217805 China 2017 93.5 8.81704560829162 7.22616015441748 5.099061489105225 1396215000 1.535146592752549 India 2017 23.3 1.95796981329558 1.70492672078233 4.046111106872559 1354195680 0.5269607712823304 New Zealand 2017 193.2 42.9109728362488 6.84049360146252 7.327182769775391 4813600 20.46462107362473 South Africa 2017 92.9 6.73447515314548 7.68370781068603 4.513655185699463 56641209 3.0294709987564 United States 2018 292.4 62.823309438197 15.2225180998504 6.882684707641602 326838199 9.478543234782665 Brazil 2018 57.8 9.12102099480377 2.06426147881772 6.190921783447266 210166592 23.745515176836477 Finland 2018 209.5 49.9876261584968 8.04918842721228 7.858107089996338 5515525 40.62895191300919 Germany 2018 161.6 47.939278288450396 8.53704268780674 7.118364334106445 82905782 1.3773466366917568 Israel 2018 129.9 42.406845426360604 6.91499302021885 6.927178859710693 8882800 0.1576079614535957 Australia 2018 228.8 57.2735204750079 15.8657135218488 7.176993370056152 24963258 53.68093379477951 China 2018 96.4 9.90540638307759 7.53319313353674 5.131433963775635 1402760000 1.5413829878240042 India 2018 24.5 1.9743777314935 1.79559529858433 3.818068742752075 1369003306 0.5232069176610155 New Zealand 2018 191.1 43.2368866923404 6.61327184426397 7.370285987854004 4900600 20.11008856058442 South Africa 2018 88.2 7.06772416484458 7.66737702463575 4.883922100067139 57339635 2.9862223573624074 United States 2019 288.4 65.1203946628653 14.6733807134556 6.943701267242432 328329953 9.43547785297554 Brazil 2019 58.9 8.84532414932264 2.05077012882977 6.451148986816406 211782878 23.505134348018444 Finland 2019 203.4 48.6298582283032 7.42303960115952 7.78034782409668 5521606 40.58420684127046 Germany 2019 156.3 46.8051384334439 7.9271876239049 7.035472393035889 83092962 1.374243946196069 Israel 2019 132.5 44.4522325623093 6.9357521537442 7.331779956817627 9054000 0.15462778882261985 Australia 2019 233.2 55.049571919719 15.5990453615115 7.233994960784912 25334826 52.893633451439534 China 2019 99.1 10.143860220595899 7.64543578560038 5.144120216369629 1407745000 1.5492763959381848 India 2019 24.8 2.0501638002619003 1.75253436625037 3.248769760131836 1383112050 0.519795919643676 New Zealand 2019 194.4 42.7964305818389 6.83005302056555 7.205174446105957 4979200 19.813464010282775 South Africa 2019 88.9 6.7025266166630395 7.68890762322173 5.034863471984863 58087055 2.9415314651431372 United States 2020 265.2 63.528634302750795 13.0328279519898 7.028088092803955 331511512 9.344924347604556 Brazil 2020 56.5 6.9236999117682 1.94252335631484 6.109717845916748 213196304 23.294006072450486 Finland 2020 197.9 49.1697193388499 6.57014512772575 7.889349937438965 5529543 40.52595304892285 Germany 2020 144.6 46.7494762280016 7.2552210281684 7.3118977546691895 83160871 1.3731217413535748 Israel 2020 121 44.8467915954816 6.34521600416707 7.194928169250488 9215100 0.15192455860489848 Australia 2020 218.4 51.8682475567823 14.7761369066259 7.1373677253723145 25649248 52.24523541586872 China 2020 101.1 10.408719554107499 7.75613790659769 5.771064758300781 1411100000 1.5589127630926227 India 2020 23.2 1.91321973278751 1.57609323191648 4.225281238555908 1396387127 0.5167621399878459 New Zealand 2020 174.3 41.7605947840005 6.16079918274331 7.257381916046143 5090200 19.434580173667047 South Africa 2020 82.7 5.75306649433369 6.68756314737781 4.946800708770752 58801927 2.899580144711924
sql_statement = """
SELECT
Country_name,
Energy_consumption_per_capita,
GDP_per_capita
FROM merged_data;
"""
pd.read_sql_query(sql_statement, connection)
| Country_name | Energy_consumption_per_capita | GDP_per_capita | |
|---|---|---|---|
| 0 | United States | 300.7 | 48.650643 |
| 1 | Brazil | 56.0 | 11.249292 |
| 2 | Finland | 242.8 | 46.505303 |
| 3 | Germany | 169.6 | 41.572456 |
| 4 | Israel | 135.0 | 31.266605 |
| 5 | Australia | 240.5 | 52.147024 |
| 6 | China | 76.2 | 4.550474 |
| 7 | India | 18.2 | 1.350634 |
| 8 | New Zealand | 188.9 | 33.676774 |
| 9 | South Africa | 102.7 | 8.059563 |
| 10 | United States | 295.4 | 50.065967 |
| 11 | Brazil | 58.0 | 13.200556 |
| 12 | Finland | 225.8 | 51.148932 |
| 13 | Germany | 163.3 | 46.705896 |
| 14 | Israel | 135.6 | 34.354716 |
| 15 | Australia | 243.3 | 62.609661 |
| 16 | China | 81.8 | 5.614386 |
| 17 | India | 19.0 | 1.449603 |
| 18 | New Zealand | 187.9 | 38.387627 |
| 19 | South Africa | 99.9 | 8.737041 |
| 20 | United States | 285.4 | 51.784419 |
| 21 | Brazil | 58.5 | 12.327513 |
| 22 | Finland | 218.5 | 47.708061 |
| 23 | Germany | 165.1 | 43.855854 |
| 24 | Israel | 139.3 | 33.156228 |
| 25 | Australia | 236.5 | 68.078044 |
| 26 | China | 84.6 | 6.300582 |
| 27 | India | 19.8 | 1.434018 |
| 28 | New Zealand | 187.1 | 39.973381 |
| 29 | South Africa | 96.9 | 8.173869 |
| 30 | United States | 290.9 | 53.291128 |
| 31 | Brazil | 60.2 | 12.258566 |
| 32 | Finland | 218.8 | 49.892223 |
| 33 | Germany | 169.3 | 46.298923 |
| 34 | Israel | 127.3 | 36.941842 |
| 35 | Australia | 235.9 | 68.198419 |
| 36 | China | 87.2 | 7.020386 |
| 37 | India | 20.3 | 1.438057 |
| 38 | New Zealand | 186.2 | 42.976650 |
| 39 | South Africa | 95.7 | 7.441231 |
| 40 | United States | 291.8 | 55.123850 |
| 41 | Brazil | 61.1 | 12.071404 |
| 42 | Finland | 210.1 | 50.327240 |
| 43 | Germany | 161.6 | 48.023870 |
| 44 | Israel | 123.2 | 38.259681 |
| 45 | Australia | 234.8 | 62.558244 |
| 46 | China | 89.2 | 7.636074 |
| 47 | India | 21.4 | 1.559864 |
| 48 | New Zealand | 192.6 | 44.572899 |
| 49 | South Africa | 95.3 | 6.965138 |
| 50 | United States | 287.0 | 56.762729 |
| 51 | Brazil | 59.7 | 8.783215 |
| 52 | Finland | 207.9 | 42.801908 |
| 53 | Germany | 163.8 | 41.103256 |
| 54 | Israel | 128.0 | 36.206522 |
| 55 | Australia | 237.0 | 56.758869 |
| 56 | China | 89.9 | 8.016446 |
| 57 | India | 21.9 | 1.590174 |
| 58 | New Zealand | 192.3 | 38.630727 |
| 59 | South Africa | 91.9 | 6.204930 |
| 60 | United States | 284.7 | 57.866745 |
| 61 | Brazil | 57.7 | 8.680736 |
| 62 | Finland | 210.9 | 43.814027 |
| 63 | Germany | 165.7 | 42.136121 |
| 64 | Israel | 128.1 | 37.690474 |
| 65 | Australia | 234.8 | 49.918794 |
| 66 | China | 91.0 | 8.094390 |
| 67 | India | 22.6 | 1.714280 |
| 68 | New Zealand | 191.7 | 40.058196 |
| 69 | South Africa | 94.8 | 5.735067 |
| 70 | United States | 283.8 | 59.907754 |
| 71 | Brazil | 57.9 | 9.896719 |
| 72 | Finland | 205.7 | 46.412136 |
| 73 | Germany | 166.7 | 44.652589 |
| 74 | Israel | 131.7 | 41.114782 |
| 75 | Australia | 230.5 | 53.954553 |
| 76 | China | 93.5 | 8.817046 |
| 77 | India | 23.3 | 1.957970 |
| 78 | New Zealand | 193.2 | 42.910973 |
| 79 | South Africa | 92.9 | 6.734475 |
| 80 | United States | 292.4 | 62.823309 |
| 81 | Brazil | 57.8 | 9.121021 |
| 82 | Finland | 209.5 | 49.987626 |
| 83 | Germany | 161.6 | 47.939278 |
| 84 | Israel | 129.9 | 42.406845 |
| 85 | Australia | 228.8 | 57.273520 |
| 86 | China | 96.4 | 9.905406 |
| 87 | India | 24.5 | 1.974378 |
| 88 | New Zealand | 191.1 | 43.236887 |
| 89 | South Africa | 88.2 | 7.067724 |
| 90 | United States | 288.4 | 65.120395 |
| 91 | Brazil | 58.9 | 8.845324 |
| 92 | Finland | 203.4 | 48.629858 |
| 93 | Germany | 156.3 | 46.805138 |
| 94 | Israel | 132.5 | 44.452233 |
| 95 | Australia | 233.2 | 55.049572 |
| 96 | China | 99.1 | 10.143860 |
| 97 | India | 24.8 | 2.050164 |
| 98 | New Zealand | 194.4 | 42.796431 |
| 99 | South Africa | 88.9 | 6.702527 |
| 100 | United States | 265.2 | 63.528634 |
| 101 | Brazil | 56.5 | 6.923700 |
| 102 | Finland | 197.9 | 49.169719 |
| 103 | Germany | 144.6 | 46.749476 |
| 104 | Israel | 121.0 | 44.846792 |
| 105 | Australia | 218.4 | 51.868248 |
| 106 | China | 101.1 | 10.408720 |
| 107 | India | 23.2 | 1.913220 |
| 108 | New Zealand | 174.3 | 41.760595 |
| 109 | South Africa | 82.7 | 5.753066 |
result = merged_data.groupby('Country_name')[['Energy_consumption_per_capita', 'GDP_per_capita']].mean()
print(result)
Energy_consumption_per_capita GDP_per_capita Country_name Australia 233.972727 58.037723 Brazil 58.390909 10.305277 China 90.000000 7.864343 Finland 213.754545 47.854276 Germany 162.509091 45.076623 India 21.727273 1.675669 Israel 130.145455 38.245156 New Zealand 189.063636 40.816467 South Africa 93.627273 7.052239 United States 287.790909 56.811416
result = result.sort_values(by='Energy_consumption_per_capita', ascending=False)
fig, ax = plt.subplots()
bar_width = 0.35
index = np.arange(len(result))
bars1 = ax.bar(index, result['Energy_consumption_per_capita'], bar_width, label='Energy Consumption per Capita')
bars2 = ax.bar(index + bar_width, result['GDP_per_capita'], bar_width, label='GDP per Capita')
ax.set_xlabel('Country')
ax.set_ylabel('Values')
ax.set_title('Energy Consumption per Capita vs GDP per Capita (average 2011-2020)',fontsize=20)
ax.set_xticks(index + bar_width / 2)
ax.set_xticklabels(result.index, rotation=45, ha='right')
ax.legend()
sns.despine()
plt.tight_layout()
plt.show()
result['PerEnergyGdp'] = result['GDP_per_capita'] / result['Energy_consumption_per_capita']
result = result.sort_values(by='PerEnergyGdp', ascending=False)
fig, ax = plt.subplots()
bar_width = 0.35
index = np.arange(len(result))
bars = ax.bar(index, result['PerEnergyGdp'], bar_width, label='PerEnergyGdp',color="#4682B4")
ax.set_xlabel('Country')
ax.set_ylabel('GDP per Energy unit')
ax.set_title('GDP per Energy unit (average 2010-2020)',fontsize=20)
ax.set_xticks(index)
ax.set_xticklabels(result.index, rotation=45, ha='right')
ax.legend()
sns.despine()
plt.tight_layout()
plt.show()
sql_statement = """
SELECT
Country_name,
Energy_consumption_per_capita,
CO2_per_capita
FROM merged_data;
"""
pd.read_sql_query(sql_statement, connection)
result = merged_data.groupby('Country_name')[['Energy_consumption_per_capita', 'CO2_per_capita']].mean()
print(result)
Energy_consumption_per_capita CO2_per_capita Country_name Australia 233.972727 16.444963 Brazil 58.390909 2.191487 China 90.000000 7.210761 Finland 213.754545 8.606935 Germany 162.509091 8.877686 India 21.727273 1.591240 Israel 130.145455 7.941269 New Zealand 189.063636 6.877249 South Africa 93.627273 7.749749 United States 287.790909 15.494514
result = result.sort_values(by='Energy_consumption_per_capita', ascending=False)
fig, ax = plt.subplots()
bar_width = 0.35
index = np.arange(len(result))
bars1 = ax.bar(index, result['Energy_consumption_per_capita'], bar_width, label='Energy Consumption per Capita')
bars2 = ax.bar(index + bar_width, result['CO2_per_capita'], bar_width, label='CO2 per capita')
ax.set_xlabel('Country')
ax.set_ylabel('Values')
ax.set_title('Energy Consumption per Capita vs CO2 Emission per Capita (average 2011-2020)',fontsize=20)
ax.set_xticks(index + bar_width / 2)
ax.set_xticklabels(result.index, rotation=45, ha='right')
ax.legend()
sns.despine()
plt.tight_layout()
plt.show()
result['PerEnergyCO2'] = result['CO2_per_capita'] / result['Energy_consumption_per_capita']
result = result.sort_values(by='PerEnergyCO2', ascending=False)
fig, ax = plt.subplots()
bar_width = 0.35
index = np.arange(len(result))
bars = ax.bar(index, result['PerEnergyCO2'], bar_width, label='PerEnergyCO2',color="#4682B4")
ax.set_xlabel('Country')
ax.set_ylabel('CO2 Emission per Energy unit')
ax.set_title('CO2 Emission per Energy Consumption unit (average 2010-2020)',fontsize=20)
ax.set_xticks(index)
ax.set_xticklabels(result.index, rotation=45, ha='right')
ax.legend()
sns.despine()
plt.tight_layout()
plt.show()
sql_statement = """
SELECT
Country_name,
CO2_per_capita,
Forest_Area_per_capita
FROM merged_data;
"""
pd.read_sql_query(sql_statement, connection)
result = merged_data.groupby('Country_name')[['CO2_per_capita', 'Forest_Area_per_capita']].mean()
print(result)
CO2_per_capita Forest_Area_per_capita Country_name Australia 16.444963 55.695227 Brazil 2.191487 24.595366 China 7.210761 1.526201 Finland 8.606935 40.923702 Germany 8.877686 1.395612 India 1.591240 0.536528 Israel 7.941269 0.180578 New Zealand 6.877249 21.225550 South Africa 7.749749 3.117746 United States 15.494514 9.666301
result = result.sort_values(by='CO2_per_capita', ascending=False)
fig, ax = plt.subplots()
bar_width = 0.35
index = np.arange(len(result))
bars1 = ax.bar(index, result['CO2_per_capita'], bar_width, label='CO2 per capita')
bars2 = ax.bar(index + bar_width, result['Forest_Area_per_capita'], bar_width, label='ForestArea per capita')
ax.set_xlabel('Country')
ax.set_ylabel('Values')
ax.set_title('CO2 per Capita vs ForestArea per capita (average 2011-2020)',fontsize=20)
ax.set_xticks(index + bar_width / 2)
ax.set_xticklabels(result.index, rotation=45, ha='right')
ax.legend()
sns.despine()
plt.tight_layout()
plt.show()
result['PerCO2ForestArea'] = result['Forest_Area_per_capita']/result['CO2_per_capita']
result = result.sort_values(by='PerCO2ForestArea', ascending=False)
fig, ax = plt.subplots()
bar_width = 0.35
index = np.arange(len(result))
bars = ax.bar(index, result['PerCO2ForestArea'], bar_width, label='Forest Area per CO2 unit',color="#4682B4")
ax.set_xlabel('Country')
ax.set_ylabel('Forest Area per CO2 unit')
ax.set_title('Forest Area per CO2 Emission unit (average 2010-2020)',fontsize=20)
ax.set_xticks(index)
ax.set_xticklabels(result.index, rotation=45, ha='right')
ax.legend()
sns.despine()
plt.tight_layout()
plt.show()
sql_statement = """
SELECT
Country_name,
GDP_per_capita,
Life_ladder
FROM merged_data;
"""
pd.read_sql_query(sql_statement, connection)
result = merged_data.groupby('Country_name')[['GDP_per_capita', 'Life_ladder']].mean()
print(result)
GDP_per_capita Life_ladder Country_name Australia 58.037723 7.278955 Brazil 10.305277 6.605715 China 7.864343 5.181462 Finland 47.854276 7.583703 Germany 45.076623 6.949864 India 1.675669 4.277814 Israel 38.245156 7.240673 New Zealand 40.816467 7.277628 South Africa 7.052239 4.749302 United States 56.811416 7.019924
result = result.sort_values(by='GDP_per_capita', ascending=False)
fig, ax = plt.subplots()
bar_width = 0.35
index = np.arange(len(result))
bars1 = ax.bar(index, result['GDP_per_capita'], bar_width, label='GDP per capita')
bars2 = ax.bar(index + bar_width, result['Life_ladder'], bar_width, label='Happiness')
ax.set_xlabel('Country')
ax.set_ylabel('Values')
ax.set_title('GDP per Capita vs Happniess Indicator (average 2010-2020)',fontsize=20)
ax.set_xticks(index + bar_width / 2)
ax.set_xticklabels(result.index, rotation=45, ha='right')
ax.legend()
sns.despine()
plt.tight_layout()
plt.show()
sql_statement = """
SELECT
Country_name,
Energy_consumption_per_capita,
GDP_per_capita,
CO2_per_capita,
Life_ladder,
Population,
Forest_Area_per_capita
FROM merged_data
WHERE year = 2020;
"""
data_2020=pd.read_sql_query(sql_statement, connection)
data_2020_sorted = data_2020.sort_values(by='Energy_consumption_per_capita', ascending=False)
plt.barh(data_2020_sorted['Country_name'] + ' - Energy', data_2020_sorted['Energy_consumption_per_capita'], color='r', label='Energy Consumption')
plt.barh(data_2020_sorted['Country_name'] + ' - GDP', data_2020_sorted['GDP_per_capita'], color='g', label='GDP per Capita')
plt.barh(data_2020_sorted['Country_name'] + ' - CO2', data_2020_sorted['CO2_per_capita'], color='b', label='CO2 per Capita')
plt.barh(data_2020_sorted['Country_name'] + ' - Life', data_2020_sorted['Life_ladder'], color='y', label='Life Ladder')
plt.barh(data_2020_sorted['Country_name'] + ' - Forest', data_2020_sorted['Forest_Area_per_capita'], color='c', label='Forest Area per Capita')
plt.xlabel('Values')
plt.ylabel('Country')
plt.title('2020 Data by Country',fontsize=20)
plt.legend()
plt.grid(True)
sns.despine()
plt.show()
sql_statement = """
SELECT
Country_name,
year,
Energy_consumption_per_capita,
GDP_per_capita,
CO2_per_capita,
Life_ladder,
Population,
Forest_Area_per_capita
FROM merged_data
WHERE Country_name IN ('China', 'United States');
"""
china_us_data=pd.read_sql_query(sql_statement, connection)
plt.figure(figsize=(12, 8))
plt.suptitle('United States vs China', fontsize=20)
for i, var in enumerate(['Energy_consumption_per_capita', 'GDP_per_capita', 'CO2_per_capita', 'Life_ladder', 'Forest_Area_per_capita']):
plt.subplot(3, 2, i+1)
plot_data = china_us_data.pivot(index='year', columns='Country_name', values=var)
plot_data = plot_data[['United States', 'China']]
plot_data.plot(kind='bar', ax=plt.gca(), legend=False)
plt.title(var, fontsize=14)
plt.xlabel('Year', fontsize=12)
plt.ylabel(var, fontsize=12)
plt.tick_params(axis='both', which='major', labelsize=10)
plt.legend(['United States', 'China'], loc='upper right', fontsize=12)
sns.despine()
plt.tight_layout(rect=[0, 0.03, 1, 0.95])
plt.show()
sql_statement = """
SELECT
Country_name,
year,
Energy_consumption_per_capita,
GDP_per_capita,
CO2_per_capita,
Life_ladder,
Population,
Forest_Area_per_capita
FROM merged_data
WHERE Country_name IN ('Australia', 'New Zealand');
"""
aus_nz_data =pd.read_sql_query(sql_statement, connection)
plt.figure(figsize=(12, 8))
plt.suptitle('Australia vs New Zealand', fontsize=20)
for i, var in enumerate(['Energy_consumption_per_capita', 'GDP_per_capita', 'CO2_per_capita', 'Life_ladder', 'Forest_Area_per_capita']):
plt.subplot(3, 2, i+1)
plot_data = aus_nz_data.pivot(index='year', columns='Country_name', values=var)
# Change the order of columns
plot_data = plot_data[['Australia', 'New Zealand']]
plot_data.plot(kind='bar', ax=plt.gca(), legend=False)
plt.title(var, fontsize=14)
plt.xlabel('Year', fontsize=12)
plt.ylabel(var, fontsize=12)
plt.tick_params(axis='both', which='major', labelsize=10)
plt.legend(['Australia', 'New Zealand'], loc='upper right', fontsize=12)
sns.despine()
plt.tight_layout(rect=[0, 0.03, 1, 0.95])
plt.show()
# Export merged data to a CSV file
merged_data.to_csv('merged_data.csv', index=False)
from IPython.display import Image
Image(filename="D:/g.png", width=500, height=200)
We collected data from three resources:
2.1 Enery Consumption per Capita: United States, Australia, Finland, New Zealand are ranking top 4 as developed countries. Developing countries such like South Africa, China, Bazil, Indian have relative smaller energy consumption per capita.
2.2 GDP per Capita:developing countries such like South Africa, China, Bazil, Indian are relative smaller. China has also relative good increase. United States has very quick increase all the years.And other developed countries also have good overall increase.
2.3 CO2 Emission per Capita:Australia and United States have high CO2 emission per capita, but have big derease from 2010 to 2020.Finland, Israel and Germany have middle CO2 emission per capita, and also have big derease from 2010 to 2020. China has some increase along the years. Other countries are relative stable.
2.4 Forest Area and Forest Area per Capita: Australia has the highest forest area per capita and has clearly drease from 2010 to 2020 caused by population increase.Finland is not a big country, but its forest area per capita is ranking number 2, Brazil and New Zealand is ranking number 3 and 4 with some decrease.Other countries are relatively stable for this part.
2.5 Happiness Indicator: Finland is now the happiest country.Brazil has decreased in this area from 2010 to 2020, while China has increased at the same time period.
3.1 Filter out the data of 10 selected countries from 2010 to 2020, and check data type. Data preparation for the merging step.
3.2 Merge the data into one data set and changed the unite of some variable and calculate the new variable forest area per capita for analysis preparation.
For same energy consumption unit, Israel has the highes efficiency to have the highest GDP per capita. This indiates the technology level or industrial structure. Countries such like Germany and Australia also have higher energy efficiency. China, Indian and South Africa as developing countries have some similarity. For same energy consumption produces less GDP.
For same energy consumption unit, South Africa, China and Indian are ranking top 3 with highest CO2 emission. New Zealand did a good jod in this area with more clean energy and less CO2 emission.
For same unit of CO2 emission, Brazil has the biggest forest area to absorb the CO2 emission, Finland, Australia and New Zealand are coming after Brazil. China, Germany and Israel need more forest area for conpensation of the CO2 emission.
In general higher GDP per Capita is related to happiness. On the other hand, the gap of happiness indicator is not so big as the gap of GDP per capita.
For GDP per capita, China, South Africa, Brazil and Indian still have big gap compared to other developed countries. For CO2 emission per capita, Brazil and Indian are much smaller in 2020 compared to other countries. For forest area per capita, Brazil plays a good role campared to its energy consumption per capita. And Australia, Finland and New Zealand have also good status. United States has relative smaller forest per capita compared to its energy consumption per capita in 2020.
China has obviousely lower energy consumption per capita compared to United States from 2010-2020, and even lower GDP per capita compared to United States.For CO2 emission per capita, China is also lower than United States, but even lower forest area per capita compared to United States.Fore happiness indicator, China is a little lower than United States for all these years, but has relative quick increase from 2010 to 2020.
New Zealand has a little lower energy consumption per capita compared to Australia from 2010-2020, and also lower GDP per capita. For CO2 emission per capita, New Zealand is also lower than Australia. Compared the energy consumption per capita with Australia,good performance of New Zealand. But also has lower forest area per capita compared to Australia.Fore happiness indicator, New Zealand and Australia are on same level.